mcp-adr-analysis-server

Server Quality Checklist

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Latest release: v2.14.3
Disambiguation1/5
The tool set has many overlapping functions, such as multiple analyze_* tools (analyze_project_ecosystem, analyze_content_security, analyze_environment, analyze_deployment_progress, analyze_adr_timeline) and multiple validate_* tools (validate_adr, validate_adr_compliance, validate_all_adrs, validate_rules). Agents will struggle to differentiate between tools that appear to serve nearly identical purposes, leading to high misselection risk.
Naming Consistency2/5
While many tools follow a verb_noun pattern, there are inconsistencies such as 'smart_score', 'mcp_planning', 'tool_chain_orchestrator', and 'get_adr_context' vs 'get_server_context'. The presence of near-duplicate names like 'validate_adr' and 'validate_adr_compliance' further breaks consistency.
Tool Count1/5
With 63 tools, this server far exceeds the typical range (3-15) and even the 'too many' threshold (25+). The sheer volume makes it impractical for an agent to efficiently discover and select the correct tool, and many tools appear to be variations or extractions from the same underlying concepts.
Completeness3/5
The domain of ADR analysis and management is broadly covered, including generation, validation, aggregation, and monitoring. However, the coverage is scattered across many redundant tools, and some lifecycle actions like explicit ADR deletion are only indirectly handled through status updates or stale task management.
Average 3.4/5 across 63 of 63 tools scored. Lowest: 2.1/5.
See the Tool Scores section below for per-tool breakdowns.
- 166 of 166 community issues answered or closed in the last 6 months
- 387 commits in the last 12 weeks
- Last stable release on September 4, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds no further behavioral context such as output format, execution time, or side effects. Since annotations handle safety, the description offers minimal added value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure and fails to front-load critical information. For a tool with 10 parameters and complex behavior, this is under-specification rather than effective conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 10 parameters, no output schema, and multiple siblings, yet the description provides only a one-line summary. It does not explain return values, usage context, or the meaning of 'ecosystem analysis,' making it severely incomplete for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all 10 parameters are documented. The description itself does not add any parameter-specific meaning or clarify relationships between parameters, so it remains at the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it performs 'comprehensive recursive project ecosystem analysis' with specific techniques, but does not define what 'ecosystem analysis' includes or how it differs from siblings like analyze_environment or get_architectural_context. The purpose is clear at a high level but lacks specificity to distinguish it from other analysis tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention any prerequisites, target scenarios, or exclusions, leaving the agent without any direction on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotation Contradiction: annotations declare readOnlyHint=true and destructiveHint=false, meaning the tool should not modify state. The description explicitly states it "automatically sets up ADR infrastructure if missing," which implies creating or modifying files/state. This is a direct contradiction and seriously misleads the agent. No additional behavioral context is given to resolve this.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loads the main retrieval purpose, but the trailing phrase "provides outcome-focused workflow for project success" is vague filler that does not earn its place. The second behavior about ADR infrastructure setup is packed awkwardly into the same sentence, making the overall structure muddied despite being brief.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description must explain what the agent can expect from this tool. It does not describe return values, what "outcome-focused workflow" concretely delivers, or what happens when ADR infrastructure is missing. The contradiction with readOnlyHint further damages completeness, leaving the agent unable to safely predict side effects or output shape.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents filePath and includeCompliance. The description adds only incidental alignment with these parameters ("specific files or the entire project", "compliance checks") but does not provide any deeper semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The core action is clear: "Get detailed architectural context for specific files or the entire project." This names a specific resource and scope. However, the description then adds unrelated-sounding behaviors (ADR setup and "outcome-focused workflow"), and it does not differentiate the tool from siblings like get_adr_context or analyze_project_ecosystem.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus the many siblings, such as get_adr_context, analyze_project_ecosystem, or get_workflow_guidance. The phrase "automatically sets up ADR infrastructure if missing" hints at a conditional scenario, but there is no explicit when/when-not guidance or alternative recommendation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint: false, so the description does not need to restate that this mutates state. However, it adds no behavioral context beyond a vague 'incorporate': it does not say whether ADR files are modified, whether updates are generated before being applied, whether confirmation is needed, or what side effects occur.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single tight sentence with no filler or repetition. It is concise, though this conciseness comes at the cost of omitting useful operational detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 8 parameters, 2 enums, no required parameters, and no output schema, this one-sentence description is inadequate. An agent cannot determine what inputs are needed, what 'incorporate' does mechanically, what output to expect, or how analysisType changes behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema fully documents each parameter, giving a baseline of 3. The description adds minimal semantic value beyond connecting 'research findings' to the researchFindings parameter and 'architectural decisions' to ADR-related parameters, but it does not clarify enums like analysisType or updateType.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('incorporate') and resource ('research findings into architectural decisions'), but 'architectural decisions' is vague and does not explicitly say it updates ADR records. It is distinguishable from research-gathering siblings like perform_research, but not clearly differentiated from ADR generation/update tools without opening the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus alternatives such as perform_research, generate_adr_from_decision, or request_action_confirmation. The description does not state that research should be gathered first, whether this tool updates existing ADRs, or what conditions would make a sibling tool more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description hints at mutation ('load ADRs into memory system', 'manage'), which is consistent with readOnlyHint=false — no contradiction. However, it does not disclose that load_adrs can force reloads or that create_snapshot persists state, so the side effects of these write actions are left undisclosed. The annotations are sparse, so the description should carry more weight than it does.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The first sentence ('Advanced memory loading tool for the memory-centric architecture') is marketing fluff with no informational value. Sentences 2 and 3 are redundant — both describe querying and loading. The whole description could be compressed to a single sentence without loss of meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a complex multi-action tool (6 actions, nested query object, 5 top-level params) with no output schema and minimal annotations. The description fails to explain action semantics (what get_intelligence or create_snapshot do), output format, or how the query object interacts with the action parameter. An agent cannot reliably choose the correct action from the description alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with detailed descriptions for every parameter (tags, sortBy, entityTypes, contextFilters, etc.), so the baseline of 3 applies. The description adds zero parameter information. Notably, the six action enum values (load_adrs, get_intelligence, create_snapshot, etc.) are only described generically as 'Memory operation to perform' — the description could clarify what each action does but does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a general purpose (query, explore, manage memory entities; load ADRs) but is scattered across multiple verbs without a single clear responsibility. It names specific capabilities like loading ADRs and performing intelligent queries, but does not differentiate from siblings such as get_knowledge_graph, expand_memory, or get_memory_stats, which appear to overlap heavily.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description never mentions sibling tools, exclusions, or usage context. With 60+ siblings including expand_memory, get_memory_stats, and query_conversation_history, an agent has no basis to select this tool over them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose side effects, whether the tool modifies data, or what output format to expect. The annotations indicate readOnlyHint: false and destructiveHint: false, but the description itself is silent on these aspects. An agent cannot infer whether the tool returns instructions, applies them, or triggers side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of a single sentence that directly states the primary action. No redundant filler or verbose language is present, which is ideal for a tool definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks essential context such as expected output format, dependencies on other tools, or whether this is part of a larger masking workflow. Without this, an agent may struggle to integrate the tool correctly, especially given the large number of sibling tools with overlapping functionality.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all three parameters (content, detectedItems, maskingStrategy) with descriptive names and short descriptions, achieving 100% coverage. However, the tool description adds no extra meaning beyond the parameter names and descriptions. The 'maskingStrategy' enum is self-explanatory, but the description does not clarify how the strategy affects the output.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('Generate') and resource ('masking instructions for detected sensitive content'), but it is vague about what constitutes 'masking instructions' and does not differentiate from sibling tools like 'apply_basic_content_masking' or 'configure_output_masking'. An agent may be uncertain about the exact purpose without deeper context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description mentions 'detected sensitive content' but does not clarify whether this tool is for generating instructions only, or if it also applies the masking. There is no mention of prerequisites, typical use cases, or when to prefer sibling masking tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotation Contradiction: the description discloses mutating effects — 'Writes CHANGELOG.md, creates GitHub Releases and Milestones' — while the annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. Writing a file and creating GitHub resources are write operations that directly contradict read-only semantics; creating Releases/Milestones is also not reliably idempotent. This inconsistency could lead an agent to treat a mutating tool as side-effect-free.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Four short sentences totalling roughly 40 words, with the core purpose front-loaded in sentence one. Each subsequent sentence adds a distinct type of information: capabilities, project-type support, and external effects. Minor filler: 'Supports greenfield and brownfield projects' doesn't affect invocation behavior, but the overall size is appropriate for a multi-operation tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 21 parameters, 9 distinct operations, no output schema, and contradictory annotations, the description is too thin. It doesn't differentiate the nine operations, doesn't explain the gh CLI dependency beyond schema hints, and leaves the read-only contradiction unresolved. An agent cannot reliably choose an operation or predict state changes without opening the schema and inferring behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% — all 21 parameters carry individual descriptions and two have enums, so the schema does the heavy lifting. The description adds a small amount of context (CHANGELOG.md maps to writeToFile, GitHub Releases to createGithubRelease, local persistence fallback to localOnly) but doesn't systematically map operations to their parameters. The baseline 3 is appropriate when the schema fully documents params.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource ('Track releases mapped to ADR decisions') and enumerates concrete capabilities: generates changelogs, manages milestones, compares releases, and assesses release readiness. It names tangible outputs (CHANGELOG.md, GitHub Releases, Milestones), making the tool's function clear. It doesn't explicitly differentiate from adjacent siblings like deployment_readiness or analyze_deployment_progress, but the ADR linkage and named outputs largely carry the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives; it never names a sibling or an exclusion condition. With 61 siblings that include adjacent tools like deployment_readiness, analyze_deployment_progress, and smart_git_push, and a 9-operation surface, the absence of when-to-use/when-not-to-use direction is a real gap. The agent must infer usage entirely from the operation enum.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile with readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description doesn't need to restate those. However, the description adds no extra behavioral context, and the word 'catalog' could ambiguously suggest a persistent write, though annotations clarify it is read-only and idempotent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no filler or redundancy, which is good. However, it is so short that it leaves out useful context, so it sits at the borderline between appropriately concise and under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no description of what the tool returns, so an agent may not know what 'catalog' produces or how includeContent alters the result. The tool has low complexity and no required parameters, which mitigates the gap, but for a discovery tool with no structured output the description remains incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents both parameters with defaults and descriptions, and the description adds no additional parameter-level meaning. With 100% schema description coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Discover and catalog' and a clear resource 'existing ADRs in the project', making the core function understandable. However, it doesn't explicitly distinguish this tool from siblings like review_existing_adrs or analyze_adr_timeline beyond the word 'discover', so it loses a point on differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives, nor any mention of prerequisites such as project path configuration. The verb 'discover' implies an initial scan, but that is left to inference rather than stated explicitly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses 'optional memory integration for environment snapshot tracking' and mentions enabling 'memory entity storage', which implies write operations to a memory store. This contradicts the readOnlyHint annotation that indicates no side effects. The contradictory information undermines transparency about the tool's actual behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that covers the primary purpose and the optional memory feature. It is well-structured and front-loaded with the main action, though it could be slightly more granular without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description omits critical context: it does not describe the output format, how recommendations are presented, whether any side effects occur (beyond the memory note), or when to use this tool relative to siblings. Given the read-only annotation and the absence of an output schema, the description leaves significant gaps for an agent deciding how to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All eight parameters have descriptions, but they are minimal and mostly restate the parameter names (e.g., 'Path to project directory'). The enum values for analysisType are not explained, and nested objects like 'requirements' lack detail on structure or purpose. The descriptions provide basic help but do not add meaningful semantic depth beyond what the schema already suggests.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('analyze') and object ('environment context'), and specifies an outcome ('provide optimization recommendations'). It also mentions optional memory integration, which differentiates it somewhat from generic analysis. However, it lacks specificity about what 'environment' encompasses and how it differs from similar sibling tools like analyze_project_ecosystem.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus the many sibling analysis tools. The description does not mention alternative tools or conditions that would make this tool preferable. Users must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations indicate this is not read-only, not idempotent, and not destructive, but the description adds no behavioral context. It does not say whether existing patterns are replaced, merged, or supplemented, nor what side effects configuring patterns may have on the project. 'Configure' is vague about the actual mutation behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence with no wasted words and the main subject is front-loaded. It is appropriately concise for a tool with only two parameters, though it is so brief that it leaves behavioral details unstated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool mutates project configuration and has related sibling tools, the description is incomplete. It lacks any indication of whether existing patterns are overwritten, how the configuration is applied, what the return behavior is, or what prerequisites exist. For a configuration tool, an agent needs more than 'Configure custom sensitive patterns for a project' to invoke it confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides complete descriptions for both parameters (90-100% coverage), so the baseline is 3. The description adds almost no extra meaning beyond the schema; it merely reinforces that the tool relates to 'sensitive patterns', while the parameter names and schema descriptions carry the actual semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb-resource pair ('Configure custom sensitive patterns') and scopes it to a project, which makes the core function clear. It does not explicitly distinguish itself from the closely named sibling 'configure_output_masking', so it falls short of a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus related tools like configure_output_masking, generate_content_masking, or apply_basic_content_masking. There are no stated conditions, contexts, or exclusions, so an agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint is false, aligning with the 'Create' action, but the description does not disclose any side effects, required permissions, or potential outcomes beyond creation. No details about file overwriting, directory creation, or error conditions are provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly conveys the tool's purpose without unnecessary verbosity. It is well-structured and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks context about when or why to use this tool. It does not explain the broader workflow, what a 'research template' entails, or how it fits with sibling research tools. Given the simplicity of the operation, more context on expected outcomes would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all three parameters (title, category, researchPath) described. The description adds no extra meaning beyond the schema, but since coverage is high, the base score of 3 is appropriate per the rubric.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the primary action (Create) and the specific resource (research template file), making the tool's purpose immediately understandable. However, it does not explicitly differentiate from similar tools like 'create_rule_set' or 'generate_research_questions', though the resource type provides some distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. No mention of suitable scenarios, conditions, or why a user would choose this over sibling tools. The 'for documenting findings' clause is a mild hint but not actionable usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide only non-hints (readOnlyHint, idempotentHint, destructiveHint all false), so the description carries the burden of explaining side effects. It only restates that the tool creates something and mentions formatting, but does not disclose whether repeated calls create duplicates, whether existing rule sets are overwritten, or what persists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler or redundancy. It is concise, though somewhat under-specified; the brevity is structurally sound but not maximally useful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters, no output schema, and only generic annotations, the description is too thin. It does not explain how adrRules/patternRules relate to the creation process, what outputFormat 'both' means in behavior, or what the caller should expect after invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 7 parameters. The description adds no parameter-level meaning beyond the outputFormat concept already present in the schema, making the baseline 3 appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('Create') and resource ('machine-readable rule set') and includes the output format ('JSON/YAML format'). However, it does not differentiate this tool from similar siblings like generate_rules or configure_custom_patterns, and it omits the rule sources (ADR/pattern) visible in the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance about when to use this tool versus alternatives, no prerequisites, and no exclusions. The description is generic and does not help an agent choose between create_rule_set and similarly named rule-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only set readOnlyHint to false, which implies mutation, but the description does not disclose what 'create research tracking system' actually entails (e.g., writing files, modifying project state, persistence). The burly detail is left completely unexplained, and there is no elaboration beyond the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with a clear verb, no redundant words, and the core action is front-loaded. It is as concise as possible for the message it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a complex tool with 9 parameters, many nested objects, and no output schema. The description is far too brief to cover how the tool behaves, what it returns, or how the parameters interact. An agent would have no idea about the return format or how to properly invoke it, making this inadequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so each parameter is already described in the input schema. The description adds only the word 'context-aware', which hints at using context parameters but provides no concrete mapping or interaction guidance beyond what the schema already offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it generates research questions and creates a tracking system, which is a clear verb+resource pairing. However, it does not mention the 'context-aware' aspect in a way that differentiates it from siblings like perform_research or create_research_template, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternative siblings. It does not state when it should be chosen over perform_research, incorporate_research, or create_research_template, nor any prerequisites or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate this is not read-only and not idempotent, but the description does not clarify what side effects occur: whether rules are persisted, returned, or written to files. It also does not mention prerequisites like existing ADRs or whether the tool modifies the project. No contradiction with annotations, but the behavioral detail is thin.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no filler words. It front-loads the main action and source material. It could be slightly more structured to include output behavior, but as a concise statement it is well-formed and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With five parameters, two enums, and no output schema, the description should clarify what the tool returns or writes and how the parameters relate to the outcome. It does not mention the output format behavior, the meaning of 'source', or whether existingRules are merged or merely respected. Significant context is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so every parameter already has a meaningful description. The tool description itself adds little beyond the schema, but with complete schema coverage this is acceptable. It does not introduce any parameter-specific nuance beyond what the schema provides, hence the baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (generate), the resource (architectural rules), and the inputs (ADRs and code patterns). It is specific enough to convey the core purpose, though it does not explicitly differentiate from the sibling tool 'create_rule_set', which may overlap in function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a use case but provides no explicit guidance on when to use this tool versus alternatives like create_rule_set, validate_rules, or generate_adrs_from_prd. There are no stated conditions, exclusions, or references to sibling tools, leaving the agent to infer appropriateness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description simply restates the action labels without explaining side effects, what gets cleared, whether stats returns live data, or how invalidation affects the cache. Annotations already cover read-only feedback, idempotency, and destructiveness, and the description adds almost no behavioral context beyond the enum values.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no filler and the main actions are front-loaded. It earns a 4 rather than 5 mainly because it omits one of the defined actions, reducing completeness without affecting brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity tool with two parameters and full schema coverage, the description is minimally viable. It does not explain the meaning of each action's behavior or what the output looks like for stats, but given the simple structure and strong schema, this is an acceptable gap rather than a critical one.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents both parameters and the action enum. The description adds no additional parameter-level meaning beyond naming a few actions, so it meets the baseline but does not go further.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific resource (MCP resource cache) and the main actions (clear, stats, cleanup), which distinguishes it from all sibling tools that focus on ADRs, masking, research, or memory. However, it omits 'invalidate' from the action enum, so the purpose is clear but slightly incomplete.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, when it is appropriate to clear/cleanup/invalidate, or any exclusions. The sibling list contains no other cache-management tool, but the description still does not communicate the operational context or decision rules for selecting it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide no read-only, idempotency, or destructive guarantees, so the description carries the behavioral disclosure burden. It lists 'management' and 'tracking' features but never states whether operations create files, modify project state, require authentication, or produce persisted artifacts. This adds little behavioral context beyond what the schema already implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with a useful capability list and minimal filler. 'Enhanced' is somewhat empty, but the hyphenated list front-loads the tool's main value areas without excessive length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 26 parameters, 6 operation modes, nested objects, and no output schema, this description is too thin. It fails to explain how operations are selected, what outputs or report formats to expect, what the required `projectPath` represents, or how the various boolean flags interact. An agent would need deep schema inspection to use this safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description's feature list loosely maps to the operation enum values (e.g., 'resource allocation' maps to manage_resources, 'reporting' maps to generate_reports), but it adds no concrete parameter-level guidance or workflow context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a clear domain ('project planning and workflow management') and lists six concrete capability areas: phase management, resource allocation, progress tracking, risk analysis, and reporting. This distinguishes it from the ADR-focused and content-focused sibling tools, though it stops short of naming a single primary verb or the `operation` parameter that selects among its functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to choose this tool over alternatives, when not to use it, or how the `operation` parameter routes to different workflows. Given the large sibling list, the absence of any comparison or exclusion leaves the agent to infer usage from the schema alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, but the description advertises operations such as recalculate, sync, optimize, and reset scores. Schema parameters like forceUpdate, updateSources, recalculateAfterReset, and customWeights further suggest state-changing behavior and side effects on other tools, directly contradicting the read-only annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that front-loads the central coordination purpose and enumerates the key operation categories. It is efficient, though it sacrifices operational clarity for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 18 parameters, seven operations, nested objects, and no output schema, the description is far too thin to guide correct invocation. It does not explain when each operation is appropriate, what side effects occur, how parameters interact, or what the tool returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and each parameter includes an operation-specific description, so the schema already carries the semantic load. The tool description adds no additional parameter meaning beyond restating the coordinated scoring theme, which is acceptable given the schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies a clear resource (project health scoring system) and lists the main actions: recalculate, sync, diagnose, optimize, and reset scores. It is broad and does not explicitly differentiate from sibling tools, but it conveys the overall purpose of the tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Central coordination... across all MCP tools' implies that this tool should be used when orchestrating scoring-related operations. However, it does not provide explicit when-to-use or when-not-to-use guidance, nor does it name alternatives for individual scoring operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=false and destructiveHint=false, but the description doesn't add behavioral context beyond saying it 'generates plans'. It remains unclear whether the tool actually executes the planned tools or only returns the plan. The vague 'AI-powered' wording doesn't clarify side effects or response behavior, leaving the agent uncertain about its operational characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no redundancy. It front-loads the core concept ('AI-powered dynamic tool sequencing') and immediately states the action ('generate structured tool execution plans'). This is an exemplary model of brevity and clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the schema is fully described, the description omits essential context such as the format or structure of the output plan, whether the plan includes tool parameters, and any limitations (e.g., if only certain tools are supported). Since there is no output schema, the description should compensate but doesn't, leaving the agent uncertain about the expected return value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100% (all six parameters have descriptions), so the baseline is 3. The description adds no additional meaning to the parameters beyond what's already in the schema, such as clarifying how 'contextHints' or 'executionMode' affect plan generation. It doesn't provide extra semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: it analyzes user requests and generates structured tool execution plans. It uses a specific verb ('generate') and resource ('tool execution plans'), distinguishing it from the many domain-specific sibling tools. However, it doesn't explicitly differentiate from other planning tools like 'mcp_planning' or 'interactive_adr_planning', so it's not fully unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios, prerequisites, or why a user would choose it over sibling planning tools. This is a significant gap for an orchestrator that likely competes with similar tools in the list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description essentially restates the tool's name ('Validate that content masking was applied correctly') without adding behavioral details such as return value format, error behavior, or what 'correctly' entails. It adds minimal value beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that is front-loaded with the action ('Validate...'). Every word earns its place, with no redundancy or filler. It is appropriately sized for a straightforward validation tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description should inform the agent about what the tool returns (e.g., boolean, success message, error). It also lacks any context about when to use it (e.g., after masking generation) or how to interpret results. The description is inadequate for an agent to know how to act on the outcome, making it incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% – both parameters have descriptions ('Original content before masking' and 'Content after masking'). The description adds nothing beyond the schema, so the baseline of 3 applies. There is no additional semantic context provided about how these parameters interact.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear action ('Validate') and a specific resource ('content masking'), which distinguishes it from validation tools for ADRs or rules. However, it does not elaborate on what constitutes 'applied correctly' (e.g., comparison of original and masked content), leaving some ambiguity. It is still distinctly about content masking validation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. It does not mention that it is meant to be called after masking generation or application, or any prerequisites (e.g., having both original and masked content). No alternatives or exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not contradict the readOnlyHint annotation and adds a small amount of context: the cloud/DevOps analytical perspective and the fact that findings are meant to be persisted later via get_server_context. However, it does not disclose operational details such as file read scope, analysis depth semantics, or side effects beyond the annotation's read-only signal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the core purpose, followed by a useful actionable TIP. The 'cloud/DevOps expertise' phrase is slightly generic but does not add meaningful bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has six parameters and no output schema, so the description carries more responsibility to explain what the review produces. It only mentions 'findings' without describing their structure, and it does not clarify how analysisDepth affects output or how specificAdr is matched. The agent must infer too much from the name and schema alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the description's omission of parameter details is acceptable. It adds no additional meaning about how projectPath, adrDirectory, or analysisDepth interact, but the schema already documents these sufficiently.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific action ('Review') on a defined resource ('existing ADRs') with an explicit comparison target ('actual code implementation'). It is reasonably distinct from sibling tools like validate_adr or suggest_adrs, though it doesn't name them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrasing implies when the tool is relevant—checking ADRs against implementation—but it provides no explicit when-to-use guidance, exclusions, or alternative sibling tools. The TIP about get_server_context is follow-up workflow advice, not selection guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds useful context: security-focused push, credential detection, file filtering, and deployment metrics tracking. It also states that tests must be run by the AI, which is a notable behavioral requirement. However, it fails to disclose blocking behavior on security/test failures or the dangerous forceUnsafe and skipSecurity overrides, which are critical for safe use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loads the core purpose. The second sentence about tests is awkward and vague, but overall there is no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 7 parameters, a nested object, and destructive overrides, the description is too sparse. It does not explain the dangerous forceUnsafe and skipSecurity flags, nor the conditions under which security blocks are applied. With no output schema and minimal behavioral detail, an agent cannot fully assess the tool's risks.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% parameter description coverage, so the baseline is 3. The description adds no meaningful parameter semantics beyond the schema; the test-results instruction loosely maps to testResults but does not explain the nested structure or requirements.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies a specific operation: a security-focused git push with credential detection, file filtering, and deployment metrics tracking. It distinguishes itself from typical git push tools and the sibling set, though it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit guidance on when to use this tool vs alternatives, nor any exclusions. The instruction 'Tests should be run by calling AI and results provided' implies a required workflow but does not help an agent decide between this and siblings like release_tracking or deployment_readiness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the main behavioral risks. The description adds that the tool can 'verify completion with outcome rules,' which is a useful behavioral hint, but it does not explain what the verification outputs look like or how it handles incomplete data. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence with no filler or redundancy. It front-loads the main action and then adds the distinguishing verification aspect, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 10 parameters and no output schema, the description does not specify expected return values, default behavior, or which inputs are necessary for a meaningful analysis. The annotations cover safety, but the agent is left without enough context about what the tool will produce or how to interpret its results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% parameter description coverage, including defaults, enums, and type details, so the schema already carries the semantic weight. The description only loosely echoes the 'outcomeRules' parameter without adding new meaning or clarifying how parameters interact.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Analyze') and a clear resource ('deployment progress'), and adds a distinct verification aspect ('verify completion with outcome rules'). It is clear about the tool's core function, though it does not explicitly distinguish itself from overlapping sibling tools like deployment_readiness or release_tracking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. It merely states what the tool does, leaving the agent to infer appropriate usage from the tool name and sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already signal readOnlyHint=false, destructiveHint=false, and idempotentHint=false, so the safety profile is ambiguous. The description adds the concept of a tiered response and expansion via an expandable ID, but it does not disclose side effects, whether 'expand' modifies stored content, or any prerequisites. There is no contradiction with annotations, but the behavioral context remains thin.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with the phase marker front-loaded. It is concise, free of filler, and lets the key concept ('expandable ID') stand out immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, and the description does not explain what 'expand' returns, how the optional section and includeContext parameters affect the result, or what a tiered response looks like. An agent cannot fully judge the outcome or whether it has all necessary inputs, making the definition incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter already described (e.g., 'Expandable ID from a tiered response'). The description does not add meaning beyond the schema; it merely restates the mechanism, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Retrieve and expand stored content') and identifies the unique resource ('tiered response' with an expandable ID). It distinguishes itself from a sibling like expand_analysis_section by referencing the tiered-response workflow, though it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The 'Phase 3' prefix implies a workflow stage, but the description provides no explicit when-to-use guidance, no exclusions, and no reference to alternatives such as expand_analysis_section or memory_loading. An agent must infer the intended context from the phrase 'tiered response,' which is not stated as a usage rule.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are all false, offering no safety hints. The description does not disclose side effects like file overwriting, permissions, or idempotency behavior. It mentions a merge workflow but that is an instruction to the agent, not the tool's own behavior, leaving the tool's actual side effects opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately sized, front-loading the purpose and then adding a critical workflow instruction. The example URLs add specificity but could be trimmed; overall it is structured with a clear critical warning and is not overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 7 optional parameters well-documented in the schema, and no output schema. The description provides crucial context about merging base repository code, but does not cover behaviors like existing file handling, the relationship between scriptType and generated scripts, or how customValidations integrate. It is adequate but has gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-specific meaning beyond the schema, such as how parameters interact or any special constraints. It does not compensate for the schema's already adequate coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates bootstrap.sh and validate_bootstrap.sh scripts to ensure deployed code follows ADR requirements. The verb+resource is specific and distinguishes it from validation tools like validate_adr, though it does not explicitly name a sibling for contrast.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a critical prerequisite (use WebFetch to query the base repo and merge code) but does not explicitly state when to use this tool vs alternatives or when not to use it. The context is clear for the intended workflow but lacks explicit exclusions or alternative selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnly=false and destructive=false, but description does not clarify side effects (e.g., whether it writes files, modifies state). No mention of output format or return value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and to the point, with no irrelevant details. The tip is helpful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description does not explain what happens after generation (e.g., file writing, output format, return value). Since there is no output schema, this is a significant gap for an agent to understand the tool's effect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema includes descriptions for all parameters (adrDirectory, decisionData, existingAdrs, templateFormat), but the tool description does not add extra context. The 'decisionData' nested object is somewhat self-explanatory but not enhanced.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific action (generate ADR) and input (decision data). However, it does not contrast with sibling tools like generate_adrs_from_prd or generate_adr_bootstrap, so less explicit about when to choose this one.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a tip to reference context file, but does not give explicit guidance on when to use this tool vs alternatives. Lacks conditional usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no behavioral context beyond that—no mention of what kind of output to expect, any limitations, or how recommendations are generated. With annotations present the bar is lower, but the description contributes no extra transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words and front-loads the core purpose. Minor marketing fluff like 'intelligent' and 'efficiently' slightly reduces precision, but overall it is appropriately sized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a lightweight advisory tool with fully documented parameters, the description conveys the basic purpose. However, it does not explain what the guidance output looks like (e.g., a list of tools, step-by-step plan) and does not help disambiguate from the numerous sibling guidance tools, leaving some uncertainty for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all five parameters. The description only echoes 'goals and project context' from the two required parameters and adds no additional meaning or syntax details beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('workflow guidance and tool recommendations'), and notes it is based on goals and project context. However, it does not distinguish itself from sibling tools like get_development_guidance or generate_deployment_guidance, which likely offer similar guidance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied through the parameter descriptions and the general statement about goals/project context. The description does not explicitly state when to prefer this tool over alternatives, nor does it mention exclusions, leaving the agent to infer the intended use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint=false, the annotations are neutral and carry little safety information, so the description bears the burden. It does add behavioral context beyond the annotations: the multi-phase guided workflow, research integration, option evaluation, and automatic ADR generation. However, it does not disclose side effects such as whether TODOs or ADR files are written to disk, or whether sessions persist state — meaningful gaps for a tool with generateTodos and generate_adr operations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler. The primary purpose is front-loaded in the first sentence, and the second sentence delivers an actionable prerequisite tip rather than decoration. It earns its length; only a slightly dense comma-separated feature list keeps it from a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 13 operations, 6 parameters, and no output schema, the description gives a solid high-level orientation but leaves the session orchestration implicit — the agent must infer the start/continue/provide_input/.../complete lifecycle from the operation enum alone. The TIP about reading project context partially compensates by pointing the agent to external grounding, but return behavior and the phase-by-phase contract are unexplained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3; the schema already documents input, operation, sessionId, projectPath, autoResearch, and generateTodos. The description adds no parameter-specific meaning beyond loosely mirroring the workflow (research integration maps to autoResearch/request_research, ADR generation maps to generate_adr). It neither compensates for gaps nor contradicts the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb+resource: it is an 'Interactive guided ADR planning and creation tool' that 'walks users through structured decision-making process.' The 'interactive guided' framing implicitly differentiates it from batch/one-shot siblings like generate_adrs_from_prd and suggest_adrs, though it never names them explicitly, so the differentiation is implicit rather than explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The only usage guidance is the TIP to read @.mcp-server-context.md before starting, which is a useful prerequisite but does not address tool selection. There is no statement of when to use this tool versus the many ADR-related siblings (generate_adrs_from_prd, suggest_adrs, generate_adr_from_decision), no exclusions, and no conditions. The agent must infer usage context from the name and operation enum.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds no behavioral detail beyond implying read-only retrieval, such as result ordering, pagination, or session matching semantics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundant wording. However, the 'Phase 3:' prefix is unexplained and carries little descriptive weight, preventing a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a fully documented schema and safety annotations, the tool is callable, but the absence of an output schema and the lack of clarification about what a 'conversation session' contains or how this relates to get_conversation_snapshot leaves notable gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters are already well documented in the input schema. The description only says 'based on filters' and does not add meaning beyond what the schema provides, matching the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear action ('Search and retrieve') and a specific resource ('conversation sessions') with filters. It is not a tautology, but it does not differentiate from the similarly named sibling get_conversation_snapshot.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives like get_conversation_snapshot or expand_memory. 'Phase 3' hints at a workflow but does not explain selection criteria or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds no extra behavioral detail, such as whether the tool returns a report, how violations are reported, or whether it scans a single file or the whole project. It does not contradict the annotations, but it also does not enrich them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single tight sentence with zero filler. The verb and object are front-loaded, and every word contributes to the core meaning. It is appropriately concise for a simple validation tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With six parameters, no output schema, and two enum-typed parameters, the one-line description is insufficient. It does not explain what the tool returns, how to interpret validation results, or how this validation relates to the many sibling validation tools. An agent would need to rely on the schema and external context to understand expected behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters adequately. The description contributes no additional meaning to the parameters, such as how the 'rules' array is structured or how 'validationType' and 'format' interact. It adds no value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb, 'validate', and a clear resource: 'code against architectural rules'. This differentiates it from sibling validation tools like validate_adr or validate_content_masking. However, it does not elaborate on the meaning of 'architectural rules' or the scope of validation, so it is clear but not maximally explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. With several sibling validation tools (validate_adr, validate_all_adrs, validate_content_masking), an agent cannot infer from the description which validator is appropriate for a given scenario. No prerequisites, context, or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly claims 'Re-runs are idempotent' while annotations declare idempotentHint: false, a direct contradiction that gives an agent conflicting signals about whether repeated invocations are safe and stable. The description does add useful context beyond the annotations (bounded HTML-comment preservation of manual edits, routing of deleted/superseded ADR tasks to a Stale Tasks section), but the rubric mandates a score of 1 when the description contradicts annotations. Annotation Contradiction is flagged.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three dense sentences, front-loaded with the core purpose and deliverable. Every clause earns its place: decomposition behavior, milestone linking, manual-edit boundary, idempotency, and stale-task routing. No filler, redundancy, or irrelevant preamble.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The core behavior is well covered, but for a tool with no output schema the description omits what a call returns—where TODO.md is written, success/confirmation output, or how ADRs are discovered beyond the adrDir parameter. The idempotency contradiction also weakens the completeness of the behavioral contract an agent can rely on.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all four parameters (phase, scope, adrDir, linkToMilestones) are already documented with defaults and enums. The description's TDD-pairing language adds mild semantic color to the phase parameter, and the milestone-linking mention restates what linkToMilestones already says, so the description does not materially extend the schema. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and deliverable: generate TODO.md from ADRs, then enumerates concrete behaviors (TDD task pairing, milestone linking, manual-edit preservation, stale-task handling). This clearly distinguishes it from sibling ADR-related tools like generate_adr_from_decision, suggest_adrs, and compare_adr_progress, which operate on different artifacts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The detailed behavior (decomposing ADRs into implementation tasks, preserving manual edits, tracking stale tasks) strongly implies the intended scenario: turning ADRs into actionable, maintained work items. However, the description never explicitly states when to use this tool versus related siblings such as compare_adr_progress or get_staleness_report, and names no alternatives or exclusion conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, non-mutating operation. The description adds that the validation is 'research-driven' and involves comparing findings against patterns, which gives some insight into its internal behavior. However, it does not explain what 'infrastructure reality' entails, whether external network calls are made, or what the output structure looks like. Given that annotations cover the safety profile, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences. The first sentence states the core purpose clearly, and the second provides a useful tip for consistency checks. It is front-loaded and has zero fluff. Every sentence earns its place, making it an example of efficient structuring.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is moderately complex with 5 parameters and no output schema, and the description is minimal. While annotations cover the safety profile, the description does not explain what 'research-driven analysis' entails, what 'infrastructure reality' means, or how validation results are returned. Given the tool's apparent complexity (checking against live infrastructure), the description leaves several operational details unspecified. The tip hints at consistency checks but does not fully compensate. A 3 reflects that the description is adequate but has notable gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning every parameter (adrPath, projectPath, adrDirectory, confidenceThreshold, includeEnvironmentCheck) is already documented in the schema. The description does not add any additional meaning about parameters—it merely repeats the purpose. With full schema coverage, the baseline of 3 is correct, and the description provides no extra value beyond that.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (validate), the resource (existing ADR), and the target (actual infrastructure reality), which distinguishes it from general ADR validation tools. However, it does not explicitly name sibling tools like validate_all_adrs or validate_adr_compliance to differentiate them, so it misses the explicit sibling differentiation that would earn a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives such as validate_all_adrs or validate_adr_compliance. The tip about comparing findings against patterns in @.mcp-server-context.md is operational advice, not a usage guideline. The description does not state prerequisites, exclusions, or the specific scenario where this singular validation is preferred over batch or compliance checks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral context by disclosing auto-detection of project context, adaptive thresholds, and the generation of a prioritized work queue, which helps the agent understand what happens beyond a simple read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, two sentences, and front-loads the core action before describing secondary behavior. Some phrasing such as 'smart time tracking' and 'actionable recommendations' is vague and slightly buzzword-heavy, but every sentence contributes useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main purpose and high-level outputs, and the annotations handle side-effect expectations. However, there is no output schema, no mention of return shape, and no guidance about when to prefer this over closely related sibling tools, so the definition is not fully complete for a complex, seven-parameter analysis tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters are already documented in the input schema. The description does not add detailed parameter semantics, but it does indirectly explain the purpose of context auto-detection and action generation. This matches the baseline expectation when the schema carries the burden.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the verb and resource: 'Analyze ADR timeline' and lists specific outputs such as 'prioritized work queue' based on staleness, implementation lag, and technical debt. It is more specific than a mere restatement of the title, though it does not explicitly differentiate itself from similar sibling tools like get_staleness_report or get_adr_priorities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a use case—analyzing an ADR timeline and getting recommendations—but provides no explicit when-to-use or when-not-to-use guidance. Given the large sibling list with overlapping concepts like staleness, priorities, and gap analysis, an agent gets little help choosing this tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safe, non-mutating behavior is established. The description adds the scoping behavior of comparing three inputs, but does not go beyond that; there is no contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence that names the action, the inputs, and the intended outcome with no filler or repetition. It is concise without sacrificing the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite rich schema coverage and safety annotations, the tool has 12 parameters, nested objects, and no output schema, yet the description never explains what a validation result looks like or how strictMode and validationType shape behavior. The agent is left to infer the output contract, making this incomplete for a high-complexity tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all 12 parameters, including the nested environmentConfig object, are already documented structurally. The description adds no parameter-level detail beyond naming the three subject areas (TODO.md, ADRs, environment), so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Compare') and a clear resource set ('TODO.md progress against ADRs and current environment'), making the core purpose understandable. It does not explicitly distinguish itself from sibling tools like validate_all_adrs or analyze_deployment_progress, but the comparison-oriented phrasing is distinct enough to be useful.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when implementation status needs to be validated against TODO/ADR/environment evidence, but it gives no explicit when-to-use conditions, exclusions, or alternative sibling routing. With many overlapping validation and analysis sibling tools, more guidance would help an agent choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide no meaningful safety constraints (all hints are false), so the description carries the full burden of behavioral disclosure. The description only says it 'generates' guidance, which sounds read-only, yet the schema includes generateFiles with 'Actually generate files (vs just guidance)', indicating a potentially mutating side effect. This behavioral trait is not reflected in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that names the action, resource, source, and qualifier without wasted words. It is appropriately sized for a tool whose parameter details live in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 11 parameters, no output schema, and no informative annotations, yet the description does not explain key behavioral aspects such as file generation side effects, whether the output is returned or written to disk, or how this relates to other deployment-focused tools. This creates a significant gap for an agent deciding how to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters are already well documented. The description's reference to 'environment-specific configurations' loosely aligns with the environment and includeConfigs parameters but adds no new semantic detail beyond what the schema already provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('Generate'), a specific resource ('deployment guidance and instructions'), and the source ('from ADRs'), plus a distinguishing qualifier ('environment-specific configurations'). This differentiates it from sibling tools like deployment_readiness or analyze_deployment_progress, which target different concerns.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'from ADRs' implies the tool should be used when ADRs are the basis for deployment guidance, but there is no explicit statement of when to choose this tool over related siblings such as get_workflow_guidance, get_development_guidance, or deployment_readiness. No exclusions or alternatives are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not contradict them. The description adds only the 'Phase 3' context and the notion of statistics, without detailing what metrics are included or whether the operation touches any state. With annotations covering the safety profile, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short, front-loaded sentence with no filler. Every word contributes to identifying the tool's action and subject.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read-only tool, the description is minimally viable. However, with no output schema, the vague term 'statistics' leaves the return shape undefined; an agent cannot know which metrics to expect or how to interpret them. This is a meaningful gap for a stats-focused tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters and 100% schema description coverage, so there is no parameter-semantics burden on the description. Mentioning 'stored conversation memory' provides minimal domain context, which is sufficient for a no-argument call.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb+resource: it retrieves statistics about stored conversation memory. The 'Phase 3' prefix adds workflow context, but it does not explicitly differentiate this tool from sibling memory tools like query_conversation_history or get_conversation_snapshot.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives, aside from the vague 'Phase 3' label. No exclusions, prerequisites, or sibling comparisons are provided, so an agent cannot determine when this is the right choice among the many memory-related siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context by naming Knowledge Generation + Reflexion and referencing a context file for consistency. Annotations already carry read-only/idempotent/non-destructive traits, so the bar is lower, but the description does not disclose output behavior or what 'suggest' returns.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with the primary action first and the context tip second; no filler. It is concise and scannable, though slightly jargon-heavy with 'Knowledge Generation + Reflexion'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the large number of parameters and nested objects, the description is brief but the schema is rich and annotations cover safety. It lacks a note on what the suggestion output looks like or how the various analysis modes differ, so completeness is adequate but not strong.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 11 parameters and nested fields. The description adds no parameter-level meaning beyond what the schema provides, which is acceptable but keeps this at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description names a specific verb ('Suggest') and resource ('architectural decisions'), and it names the advanced prompting approach. It clearly communicates the core function, but it does not explicitly distinguish itself from sibling generation tools like generate_adr_from_decision or generate_adrs_rom_prd.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by saying 'Suggest architectural decisions' and provides a helpful prerequisite tip to read @. mcp-server-context.md. It does not, however, give explicit guidance about when to choose this tool over sibling alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With annotations present, the description adds useful context beyond them: this is an external write to a third-party platform (URL disclosed) with two modes. However, it does not disclose that full_sync replaces/destroys existing ADRs on the remote platform, and no auth or confirmation requirements are mentioned. The destructiveHint=false annotation sits in tension with the schema's 'Replace all ADRs' semantics, though the description itself doesn't contradict the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with the action front-loaded, followed by the destination URL and purpose. Every clause earns its place; only 'optional metadata' is mildly unspecific, but it is clarified by the include_* parameters in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 8 fully-documented optional parameters, the description plus schema adequately orient the agent on what the tool does and its modes. However, with no output schema, the description omits what a successful sync returns or confirms, and it gives no caution about the irreversible external overwrite in full_sync mode — both of which matter for an agent deciding to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 8 parameters and the baseline is 3. The description's 'optional metadata' phrase loosely groups the include_* boolean flags, adding modest conceptual organization, but it does not compensate for any gaps because none exist in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Sync'), resource ('ADRs'), and destination ('ADR Aggregator platform' with an explicit URL), which unambiguously identifies the operation. The external destination effectively distinguishes it from all siblings — none of which push content to an external platform — though no sibling is named explicitly and 'with optional metadata' is vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The purpose clause ('for centralized tracking, visualization, and team collaboration') implies when an agent would choose this tool, and the 'incremental and full sync modes' note signals the two operating options. However, there is no explicit when-to-use/when-not-to-use guidance, no named alternative, and no stated prerequisite (e.g., a configured aggregator account or authentication).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate the tool is not read-only and not destructive, so the bar for additional behavioral disclosure is lower. The description adds that masking is configured globally, but does not explain that 'reset' may restore defaults, that 'get' is a read-only action, or that settings affect subsequent MCP outputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It immediately conveys the verb, the resource, and the scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a complete schema and annotations, the description is reasonably sufficient for identifying the tool. Gaps remain around practical behavior, such as what 'get' returns and what 'reset' actually resets, especially since there is no output schema or explicit usage guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and all parameters have descriptions, so the description does not need to repeat parameter details. However, it also does not clarify the semantics of the strategy values (e.g., 'environment' vs 'placeholder'), which would add value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Configure') and resource ('content masking') with an explicit scope ('all MCP outputs'), making the tool's purpose clear. It does not explicitly differentiate from sibling tools like apply_basic_content_masking or generate_content_masking, but the config terminology and global scope hint at the distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The scope of all MCP outputs implies this is for global configuration, but there is no explicit when-to-use or when-not-to-use guidance, nor mention of alternatives. An agent would infer usage from the tool name and sibling names rather than from direct instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description's safety burden is low. The description adds context that the tool returns a current snapshot for resumption/analysis, but it does not describe output shape, pagination, or any side effects beyond what annotations already cover.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. The 'Phase 3:' prefix is somewhat ambiguous outside a broader workflow, but it does not bloat the description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, read-only tool with one optional parameter, the description provides sufficient context for invocation. No output schema is present, but the purpose and resource are clear enough; more detail about what the snapshot contains would be helpful but not strictly necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameter recentTurnCount is already documented in the schema with a default and explanation. The description does not add additional meaning about how the parameter interacts with the snapshot, leaving it at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'current conversation context snapshot,' and adds the intended purpose of resumption or analysis. It does not explicitly name a sibling alternative, but 'snapshot' distinguishes it from history-querying tools like query_conversation_history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for resumption or analysis' implies when the tool is useful, and 'Phase 3' hints at a workflow position. However, it gives no explicit guidance about when not to use it or which sibling tool to choose instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description claims the tool creates a file, implying a write operation, while the annotations declare readOnlyHint: true. This direct contradiction obscures the tool's actual side effects, severely impacting transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and well-structured, immediately conveying the primary action and output without unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the purpose and output are clear, the lack of detail on parameter behavior and the contradiction with readOnlyHint leave gaps in understanding. The description does not explain the impact of different parameter values or potential side effects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All four parameters have descriptions, providing 100% schema coverage. However, the descriptions are generic and largely restate the parameter names, offering little additional semantic value beyond what the schema already implies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: generating a comprehensive context file of the server's state, memory, and capabilities. It also specifies the exact output file name and its utility for LLM awareness.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly mentions that the generated file can be @ referenced in conversations, giving a concrete use case. However, it does not compare with alternative tools or specify when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile with readOnlyHint, idempotentHint, and destructiveHint. The description adds useful behavioral context around memory integration, ADR/research suggestions, and test-command output. However, 'memory integration for troubleshooting session tracking' is ambiguous about whether the tool persists state, which creates some tension with the readOnlyHint; this isn't a direct contradiction but a meaningful gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with the core purpose front-loaded and the actionable instruction at the end. It includes some mild fluff like 'intelligent' and 'capabilities,' but overall it is reasonably compact and contains no redundant restatement of the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a complex tool with nine parameters, nested objects, three operation modes, and no output schema, yet the description remains high-level. An agent cannot tell what 'full_workflow' does differently from the other operations, what the exact return shape is, or how the memory/ADR/research features manifest in the result. The schema covers parameter structure but not behavioral completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description doesn't need to re-document parameters. It does add the useful clue that failure info should be JSON and that the output includes test commands, but it doesn't explain the three operation modes or how optional toggles like memory integration affect behavior. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies a specific purpose: structured failure analysis and test plan generation from JSON failure information. It clearly differentiates from many sibling tools by combining troubleshooting with memory integration and ADR/research suggestions, though it uses noun-phrase style rather than an explicit verb and doesn't name an alternative tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'provide JSON failure info to get specific test commands' gives a clear usage context: this tool is for analyzing a failure and producing test commands. It doesn't state explicit exclusions or when-not-to-use, but the intended scenario is reasonably clear from the description and title.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly and idempotent behavior, and the description adds a useful behavioral trait beyond them: optional memory integration for security pattern learning. It stops short of spelling out side effects such as default-on memory writes or whether learned patterns persist, but it does not contradict the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that front-loads the verb and resource, then gives two useful qualifiers: detection method and memory behavior. There is no filler or redundant restatement of the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description leaves the result format unstated, which is a significant gap for an analysis tool. It also lacks guidance differentiating it from the security-masking and validation siblings, and does not clarify whether memory integration writes persisted state by default.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all six parameters. The description only restates the top-level memory integration concept at a high level and adds no format, syntax, or default information beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Analyze content for sensitive information', making the core function immediately identifiable. It clearly contrasts with sibling masking/configuration tools by framing the operation as analysis/detection, though it does not explicitly name an alternative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The purpose statement implies the primary use case: detect sensitive information in content, which is a real usage signal. However, it gives no explicit guidance on when to prefer this over sibling tools like generate_content_masking or validate_content_masking, nor any when-not-to-use conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is handled. The description adds useful context about querying the ADR Aggregator and providing compliance metrics, but it does not disclose potential edge cases, report scope, or behavior beyond what the annotations and core purpose already imply.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. It front-loads the action, names the source, states the output type, and gives the practical purpose of identifying stale ADRs. Every clause contributes meaningful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, read-only, zero-required-parameter report tool, the description is largely complete: it describes the source, the output function, and the type of insights. There is no output schema, but the description compensates by naming the metrics. It could be stronger with an explicit statement of what the returned report contains, but the current description is sufficient for basic invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters are already well documented structurally. The description does not add extra meaning about how threshold or projectPath behave or how they affect the report, so it earns the baseline 3 rather than higher.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies a specific action ('Get'), a resource ('ADR staleness report'), the source ('ADR Aggregator'), and the deliverable ('review compliance metrics'). It is far from a tautology and tells the agent it identifies stale ADRs, but it does not explicitly contrast it with nearby sibling tools like analyze_adr_timeline or get_adr_priorities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use case is implied: use this when you need stale ADRs and governance insights. However, there is no explicit guidance about when to prefer this tool over alternatives such as analyze_adr_timeline, get_adr_priorities, or validate_adr_compliance, and no exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There is a direct contradiction between the annotation readOnlyHint: true and the parameter description for researchDirectory stating 'Directory the research document is written to.' This implies the tool writes a document, violating the read-only hint. The description fails to disclose or reconcile this side effect, and the annotation contradiction is severe.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that efficiently conveys the cascading source order and fallback. No unnecessary words or redundant details. It is well-structured and immediately understandable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool description provides sufficient context for an agent to understand its role in research tasks, especially with the cascade order. No output schema is present, but the description does not need to detail return format. However, the writing side effect is not mentioned in the overall behavior, leaving a gap in full contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 6 parameters are described in the schema with 100% coverage. Each parameter has a clear meaning: question, paths, boolean flag, and threshold. The descriptions are concise and adequate, though they do not add extra context beyond the schema. The 'researchDirectory' mention of writing is the only ambiguity, but it is tied to the parameter's purpose rather than its type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: performing research using a cascading source order. The verb 'Perform research' is specific and the resource (multiple sources) is implied. It distinguishes itself from sibling research tools by highlighting the cascading approach and web fallback.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for broad research across multiple sources, but does not explicitly state when to use this tool over alternatives like search_codebase or generate_research_questions. It lacks clear disambiguation or conditions for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description signals that the tool is interactive—it requests confirmation rather than directly applying changes—which adds behavioral context beyond the annotations. However, it does not clarify what happens after confirmation, whether the caller must apply the change separately, or any side effects beyond the confirmation request itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no filler or unnecessary detail. It is front-loaded with the core purpose and communicates the essential context efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a relatively simple interactive confirmation tool, the description captures the core purpose and timing. The schema documents all parameters, and the annotations provide safety signals, so the description is sufficiently complete for an agent to understand the tool's role.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides complete descriptions for all three parameters, including the impact enum and default value. The description adds no additional parameter-level meaning, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb and resource: it requests confirmation for an action before applying research-based changes. This distinguishes the tool as an interactive confirmation gate rather than a validation or execution tool, though it does not explicitly name sibling alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'before applying research-based changes' provides clear timing context for when this tool should be used. It does not state exclusions or explicitly compare against sibling tools like validate_adr or incorporate_research, but the intended use is reasonably evident.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false, so the description correctly aligns by describing mutating operations. It adds useful context about local JSON snapshots, keyword retrieval, and zero-cost reads, which goes beyond annotations. Still, it does not disclose side effects, persistence behavior, or operation-specific outcomes for a write tool with no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact at three sentences and front-loads the core purpose. The mention of 'ADR-018' adds a minor reference detail, but the storage model and read-alternative guidance earn their place. It is concise without being under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity — 7 parameters, 3 enums, nested objects, and no output schema — the description covers the high-level intent and read alternative. However, it does not explain which parameters are required for each operation, how metadata is used, or what happens on removal. The schema helps, but the description leaves some operational gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description adds high-level context about entity types and relationships but does not deepen understanding of parameter combinations or metadata semantics beyond what the schema provides. This matches the baseline for full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Simple CRUD operations for project session state' and specifies 'Add/remove entities (intents, ADRs, tools, code) and relationships', making the resource and actions explicit. It also distinguishes itself from a graph database, but it does not explicitly differentiate itself from a specific sibling tool, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives actionable guidance: 'Use knowledge://graph resource to read current state (zero token cost)', which tells the agent when to read rather than mutate. It also clarifies the tool's scope with 'Not a graph database — keyword retrieval over local JSON snapshots.' However, it does not explicitly name sibling tools or state when not to use this tool beyond the read case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds the fallback context but no behavioral detail: no mention of what transformation occurs, whether output is returned, or limitations of 'basic' masking. Annotations provide only readOnly/destructive hints, so the agent is left without a clear model of the tool's effect.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with a parenthetical condition. Every word earns its place and no redundant schema information is repeated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with full schema coverage, the description plus schema is mostly adequate. However, there is no output schema and no description of the return value or edge behavior, so an agent cannot fully anticipate the result of calling it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with descriptions ('Content to mask', 'Strategy for masking content') and an enum, so the baseline is 3. The description adds no parameter information, but the schema already does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a clear verb ('apply') and resource ('basic content masking'), and the parenthetical 'fallback when AI is not available' signals it is the non-AI alternative to sibling tools like generate_content_masking. This distinguishes it from nearby masking tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives an explicit usage condition: use this tool when AI is not available. It doesn't name alternatives or exclusions, but the fallback condition is enough to route an agent. Could be more explicit about when to prefer generate_content_masking.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context beyond that: 'hard blocking for unsafe deployments' and integration with smart_git_push. It does not detail override side effects or the fact that some parameters trigger migrations or health-score updates, but those are visible in the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense sentence that front-loads the tool's purpose, then names three concrete capabilities and one key integration. Every phrase earns its place, and there is no redundancy or vague filler that bloats the definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity — 24 parameters, six operation modes, and no output schema — the description provides a solid summary but leaves operational selection underspecified. It does not explain how to choose among operations like check_readiness, full_audit, or emergency_override, nor how strictMode and thresholds interact with the blocking behavior. The schema describes parameters well, but the description alone would not fully guide an agent through a realistic deployment-readiness scenario.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 24 parameters thoroughly, including their defaults and enums. The description reinforces themes like test failure tracking and deployment history analysis but does not add parameter-level detail such as when businessJustification is required for emergency_override. The baseline of 3 is appropriate because the schema carries the load.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's resource ('deployment readiness') and action ('validation'), while naming concrete capabilities: test failure tracking, deployment history analysis, and hard blocking for unsafe deployments. It also mentions integration with smart_git_push, which helps position it among siblings, though it does not explicitly contrast it with similar tools like analyze_deployment_progress.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Integrates with smart_git_push for deployment gating' implies the tool is used as part of a pre-deployment safety gate, and the emphasis on 'hard blocking for unsafe deployments' suggests when it should be invoked. However, it does not explicitly state when to use this tool versus alternatives such as release_tracking or analyze_deployment_progress, nor does it mention when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false, idempotentHint=false, and destructiveHint=false, so the write-like nature is partially covered. The description adds the behavioral detail that advanced prompting techniques (APE + Knowledge Generation) are used, which is useful, but it does not disclose side effects like file creation, overwrite behavior, or output location beyond what the schema's outputDirectory parameter implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. It identifies the action, the resource, the input, and the distinctive technique in a compact form.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has six parameters and no output schema, and the description does not explain what the caller should expect after execution, such as whether ADRs are written to disk, returned in the response, or how to locate generated files. The schema and annotations cover input details and basic safety, but the absence of output behavior leaves a meaningful gap for an agent invoking a generation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% parameter description coverage, so the baseline is 3 even without additional explanation in the tool description. The description mentions APE and Knowledge Generation, which loosely map to promptOptimization and knowledgeEnhancement booleans, but it does not add new semantic meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Generate'), a clear resource ('Architectural Decision Records'), and a distinct input source ('Product Requirements Document'). This distinguishes it from siblings like generate_adr_from_decision, which takes a decision, or generate_adr_bootstrap, which bootstraps from a template.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended context is implied by 'from a Product Requirements Document': the agent should use this tool when it has a PRD and needs ADRs derived from it. However, there is no explicit guidance about when not to use it or which alternative to prefer, such as generate_adr_from_decision or suggest_adrs, so the usage guidance remains inferred rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable behavioral context by stating the Pro+ tier requirement and specifying the types of diagrams included, which goes beyond the structured annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences with the primary purpose front-loaded. Every sentence adds relevant information: the action and source, the diagram types, and the access requirement. There is no filler, though it does not go into unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description provides a reasonable hint of expected results ('Includes workflow, relationship, and impact diagrams') and notes the access restriction. The optional parameters are covered by the schema. It is complete enough for a simple read-only retrieval tool, though it does not describe error or empty-result behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters (adr_path and projectPath) are already documented. The description adds no additional parameter-level meaning, such as value formats or interplay between the two parameters, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific verb 'Get' and the resource 'Mermaid diagrams for ADRs from ADR Aggregator', and lists the included diagram types. It does not explicitly name or differentiate against sibling tools, but the unique focus on Mermaid diagrams makes the purpose unmistakable among the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when ADR diagrams are needed, and adds a prerequisite with 'Requires Pro+ tier'. However, it does not explicitly state when to use this tool versus alternatives like get_adr_context or analyze_adr_timeline, nor does it provide exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool read-only, idempotent, and non-destructive, so the safety profile is covered. The description adds useful behavioral context beyond annotations by specifying that matches are returned as raw files with relevance scores and that the operation is atomic. This helps the agent anticipate the form and scope of results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded: the core purpose and return behavior appear in the first sentence. The second sentence provides provenance ('Extracted from ResearchOrchestrator per ADR-018') which is only marginally useful for invoking the tool, but it is short and does not distract much.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With rich annotations, fully documented parameters, and a description that states both purpose and return value shape, the definition is largely complete for a simple read-only search tool. It does not fully explain relevance scoring semantics or how 'query patterns' are interpreted, and it lacks sibling routing guidance, but those are secondary gaps for this tool type.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameter meanings and defaults. The description does not add parameter-level semantics beyond the schema, but it also does not need to under this coverage level; the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific resource ('codebase files'), a specific action ('searching'), and states the output ('raw file matches with relevance scores'). It is clear enough to distinguish from the sibling analysis and generation tools, though it does not explicitly name any sibling it should not be confused with.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool ('searching codebase files') but provides no explicit guidance about when to prefer it over alternatives or when not to use it. With over 60 sibling tools, a more direct routing statement would have been valuable, but the intended use case is reasonably inferable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already cover readOnly, idempotent, and destructive hints. The description adds a notable behavioral detail: that it 'reports gaps to ADR Aggregator for tracking', which is not captured in the annotations. This extra context informs the agent about a potential side effect (external reporting) beyond the annotated read-only nature. However, it does not elaborate on the reporting mechanism or any permissions implied, so it is not fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. It opens with a clear one-sentence summary, then breaks down the two gap types into bullet-like numbered points, and ends with the reporting behavior. There is no redundant or verbose language, and every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks information about what the tool returns to the caller. It mentions 'reports gaps to ADR Aggregator' but does not state whether the tool returns a list, a summary, or any direct output to the invoking agent. Since there is no output schema, the description should at least specify the return format or indicate that no direct output is provided. This omission leaves the agent uncertain about the tool's immediate effect and return value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides descriptions for all 6 parameters, covering 100% of them. The tool description itself does not add any extra meaning or context for the parameters; it relies entirely on the schema. Since schema coverage is high and the descriptions are adequate, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: it scans the codebase and compares with ADRs to detect two specific types of gaps (ADR-to-code and code-to-ADR). This is a specific verb (scan, compare, detect) tied to a specific resource (local codebase and ADRs), and the two gap types are explicitly enumerated. It distinguishes itself from siblings like 'get_gaps' (which likely retrieves gaps rather than analyzing them) enough for an agent to choose it correctly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool instead of alternatives. It implies the use case (finding gaps), but there is no mention of conditions like 'when you need a fresh analysis' or 'to retrieve existing gaps use get_gaps'. The description is functional but not prescriptive about scenarios or comparisons with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is fully covered structurally. The description adds modest behavioral context by naming the source (ADR Aggregator) and the bundled content categories, but it does not disclose tier-gating behavior (Team vs Pro+ features already noted in the schema) or any response-shape details. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with zero filler. The core action and content scope are front-loaded in the first sentence, and the use-case framing in the second earns its place. Nothing is redundant with the schema or annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 7-parameter read-only tool with a 100%-covered schema, a strong annotation profile, and no output schema, the description provides adequate orientation by enumerating what the response includes. The main gaps are minor: tier restrictions are mentioned only in parameter descriptions rather than the tool description, and return format is not specified — but the listed content categories partially compensate for the missing output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline of 3 applies — every parameter already carries meaningful documentation (e.g., include_diagrams is 'Include Mermaid diagrams (Pro+ tier)' and staleness_filter has an enum with default 'all'). The description loosely groups some parameters through its content list (diagrams, timeline, code links), but adds no format, syntax, or interaction semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Fetch'), resource ('ADR context from ADR Aggregator'), and enumerates the content types returned (summaries, diagrams, timeline data, code links). It also frames the value as a 'consolidated view of architectural decisions.' However, it does not explicitly differentiate from nearby siblings like get_architectural_context or get_knowledge_graph.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The second sentence ('Useful for getting a consolidated view of architectural decisions') provides a clear use case that tells an agent when to select this tool. It lacks explicit exclusions and does not name alternatives, but the context is concrete enough to guide selection without being merely implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral context by revealing the transformation pipeline and output categories (coding tasks, implementation patterns, development roadmap), which goes beyond the structured annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. It states the core purpose first and then adds the output detail in a subordinate clause, making it easy for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters, a nested object, and no output schema, the description compensates by naming the expected output kinds. It lacks explicit guidance about optional parameter interactions or return structure, but the schema and annotations cover the remaining essentials.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 86%, so the schema already documents most parameter meaning; the baseline is therefore 3. The description adds only a high-level umbrella ('architectural decisions' maps to adrsToImplement) and does not contribute specific parameter-level semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'get comprehensive development guidance' and explains it translates architectural decisions and workflow recommendations into coding tasks, patterns, and roadmap. This is clear about what the tool produces, but it does not explicitly differentiate it from sibling tools like get_workflow_guidance or generate_deployment_guidance, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied rather than explicit: the name and description signal that this is for obtaining development guidance, and the required developmentPhase parameter suggests phase-specific use. However, no when-to-use or when-not-to-use guidance is given, and no alternatives from the sibling list are referenced.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the description does not need to restate safety behavior. It adds useful context beyond annotations by naming the ADR Aggregator source, the Team tier requirement, and the inclusion of analytics and insights.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main purpose and scope, and contains no filler or tautology. The Team tier note is the only extra detail and it is directly relevant to whether the agent can successfully invoke the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only, non-destructive tool with optional parameters and rich annotations, the description is largely complete: it names the data source, the visualization purpose, the analytics feature, and the required tier. It does not describe the exact response format or return fields, but the annotations and optional-parameter schema reduce the risk of misuse.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all three parameters are already documented in the schema. The description's mention of 'analytics and insights' loosely aligns with include_analytics, but it adds no parameter-specific details such as formatting, defaults, or scope behavior beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('Get cross-repository knowledge graph from ADR Aggregator') and clarifies that it visualizes ADR relationships with analytics and insights. It reads clearly and communicates the core value, but it does not explicitly distinguish itself from closely related siblings like get_adr_diagrams or get_architectural_context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied through 'Visualize ADR relationships across repositories,' and the Team tier requirement provides a precondition. However, there is no explicit statement about when to use this tool versus alternatives, nor any when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden at least partially. It clearly marks the operation as a mutation, states a prerequisite (Pro+ tier), and limits the target to synced ADRs. It does not disclose what happens after the update, whether the change is pushed, or error behavior, so the transparency is only partial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences with the main action in the first and key constraints in the second. It is front-loaded and free of filler, though it slightly duplicates the status enum already present in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a batch mutation with no output schema, the description could say more about the result of the update, whether multiple updates are atomic, or what happens for unsynced ADRs. The Pro+ requirement and 'synced ADRs' constraint help, but the postcondition is left unclear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already defines adr_path, implementation_status, and notes. The description only repeats the status enum rather than adding new meaning about how to form the updates array, so it lands at the baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Uses a specific verb ('Update') with a clear object ('implementation status of synced ADRs') and an operating context ('directly from the IDE'). This distinguishes it from the sibling tools, which are mostly read/analysis/validation/generation operations rather than status mutations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides actionable context: the tool is meant for ADRs that are already synced and requires a Pro+ tier. It does not explicitly name an alternative or a when-not-to-use case, but the scope is constrained enough that an agent can infer the intended use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the context that validation checks against 'actual infrastructure reality', which hints at live-environment comparison, but it does not go beyond that into side effects, permissions, or failure behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word contributes to identifying the action, scope, and comparison target.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only, idempotent batch validation tool with fully documented parameters and no output schema, the description conveys the core purpose adequately. It could have mentioned what a validation result looks like, but the absence of that is a minor gap given the strong annotations and schema coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema fully documents all four parameters with defaults and descriptions. The tool description adds no parameter-specific meaning beyond the schema, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Validate'), a resource ('all ADRs in a directory'), and the criterion ('against actual infrastructure reality'). This clearly distinguishes the bulk operation from sibling 'validate_adr', which validates a single ADR.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool by saying 'all ADRs', and the sibling context offers a comparison to singular 'validate_adr'. However, there is no explicit when/when-not guidance or named alternative, so usage is inferred rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral detail beyond the annotations: the tool does not run commands internally, it iteratively processes user-provided output, it requires explicit human confirmation for platform selection, and it detects the target platform. These traits align with the readOnlyHint and destructiveHint annotations and provide the agent with essential expectations for the tool's interaction model. It does not cover every edge behavior (e.g., maxIterations behavior), but the disclosed traits are highly valuable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with bold section headers and front-loads the most critical fact (does NOT execute commands internally). Some redundancy exists, such as repeating that the tool is iterative and that the user reports back output, but overall every section contributes to the agent's understanding of the tool's operation mode. It earns a 4 rather than 5 because the moderate length and occasional repetition could be tightened.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (11 parameters, no output schema), the description covers the core interaction loop, platform detection, environment validation, human approval requirements, validated patterns integration, and cleanup guidance. Missing details like maxIterations termination, ADR update behavior, and output structure are either captured in the schema or are peripheral to the main workflow. This is a reasonably complete overview for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description reinforces the meaning of currentIteration and previousExecutionOutput by explaining the iterative flow, but it does not add new parameter-level semantics that are not already present in the schema. The workflow explanation provides useful context, but the schema descriptions already carry the detailed parameter definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's specific function: it guides an interactive, step-by-step deployment validation workflow and does NOT execute commands itself. It distinguishes itself from sibling tools by emphasizing its 'GUIDED EXECUTION MODE' and iterative command-feedback loop, which is a unique behavioral trait among the listed deployment tools. However, it does not explicitly name or compare against alternatives like deployment_readiness or troubleshoot_guided_workflow, so differentiation relies on behavioral description rather than explicit contrast.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides concrete usage context: when to make the first call (iteration=0), how subsequent calls should pass back command output, and when to request deployment cleanup for CI/CD workflows. It also specifies that human approval is required before deployment and before destructive commands may be offered. It does not, however, explicitly state when not to use this tool or mention alternative tools, so it stops short of a full when/when-not comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds beyond those by disclosing that no authentication is required and that the data comes from ADR Aggregator, which is useful context not present in annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences with no fluff: purpose, content coverage, and auth requirement are all front-loaded and relevant. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity tool with one optional parameter and strong safety annotations, the description is largely complete: it identifies source, content, domain applicability, and auth. It does not describe the return format or behavior when the domain is omitted, but these are minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description's domain examples (web applications, microservices, APIs) reinforce the domain parameter but do not add new meaning beyond the schema's own examples and 'etc.' qualifier.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Get'), a clear resource ('domain-specific ADR templates and anti-patterns'), and a source ('ADR Aggregator'). It distinguishes itself from generation-oriented siblings like generate_adrs_from_prd or suggest_adrs by focusing on retrieving templates and best practices.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when domain-specific ADR templates or best practices are needed and explicitly notes 'No authentication required.' However, it does not name alternatives or state when not to use this tool, leaving the agent to infer the choice from the resource type.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the description is not required to repeat them. It adds context about returning statuses and emphasizing 'current' data, which is useful but does not disclose additional behavioral traits beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise—two sentences that are front-loaded with the primary action. The main purpose is immediately clear, and the additional detail about return statuses is relevant and non-redundant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (a read-only getter with three straightforward parameters), the description adequately covers its function and output. It does not need to explain parameters (schema does that) or side effects (annotations do that). The description is complete for an agent to decide and invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides full coverage for all three parameters (projectPath, includeResolved, includeDismissed) with descriptions. The tool description adds no parameter-specific meaning, so it remains at the baseline of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Get'), a resource ('code gaps'), and a source ('ADR Aggregator'), and elaborates on the purpose with 'for tracking and management.' This distinguishes it from sibling tools like 'analyze_gaps' which imply analysis rather than retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving current gaps but does not explicitly state when to use this tool over alternatives. The phrase 'current' and 'tracking and management' hint at a retrieval vs. analysis distinction, but the guidance is not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds meaningful context about the tiered-response mechanism and that content is stored in memory, complementing the annotations. No contradiction found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with no filler. The first sentence front-loads the action and resource, while the second adds the usage trigger and the option to expand specific sections. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's read-only nature, full schema coverage, and low complexity, the description is largely complete. It covers what the tool retrieves, the expandable ID mechanism, and when to use it. Minor omissions like error behavior or output size are not critical for this simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all three parameters are already documented with adequate descriptions. The description reiterates the expandableId and optional section but does not add substantial new parameter semantics beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Retrieve full analysis content from tiered responses,' which names a specific verb and resource. It further clarifies scope by stating it can expand the entire analysis or specific sections, distinguishing it from sibling tools like expand_memory.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this when a tool returns a summary with an expandable ID,' giving a clear trigger condition. However, it does not name alternatives or describe when not to use the tool, so it falls short of a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations by noting the Pro+ tier requirement and the dependency on the ADR Aggregator, which are important operational constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: the first sentence states the verb, resource, and mechanism, while the second clarifies the core purpose. The tier requirement is included without clutter, and every sentence contributes useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema, the description provides enough context for invocation: what is validated, how it is done, and the Pro+ tier prerequisite. It does not explain return format or behavior when no adr_paths are provided, but the schema and annotations cover the essential operational details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully documents all three parameters, including the validation_type enum and the default for projectPath, so schema coverage is 100%. The description does not add significant per-parameter meaning beyond the general notion of validating ADR compliance, which is sufficient for the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Validate') and identifies the exact resource and focus: ADR compliance against implementation via the ADR Aggregator. It further clarifies the meaning by stating it 'Checks that code actually implements documented decisions,' which clearly distinguishes it from sibling validation tools like validate_adr or validate_all_adrs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear context for when to use this tool: when there is a need to verify that code implementation matches documented ADRs. It does not explicitly name alternatives or exclusion criteria, but the implementation-vs-documentation angle provides enough situational clarity to guide selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety and idempotency. The description adds behavioral context beyond that by specifying that the tool returns prioritized ADRs with scores, dependencies, blockers, implementation status, and gap counts, and notes the data source (ADR Aggregator). This adds meaningful detail without contradicting the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with zero fluff. The first sentence front-loads the action and purpose, while the second enumerates the outputs. Every word earns its place, and the structure is ideal for quick scanning by an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description appropriately covers return values (scores, dependencies, blockers, implementation status, gap counts). Safety behavior is covered by annotations, parameters are fully documented in the schema, and the tool's role is unambiguously stated. Nothing an agent needs to invoke it correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters (include_ai and projectPath) fully described in the input schema. The tool description does not add parameter-specific meaning, but it doesn't need to; it stays at the baseline of 3 given the schema's exhaustive coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Get'), a clear resource ('ADR priorities'), and a defined source ('ADR Aggregator'). It also distinguishes the tool from siblings by specifying its purpose (roadmap and backlog planning) and the exact return contents (scores, dependencies, blockers, implementation status, gap counts), making it clear what this tool provides versus others like get_gaps or get_adr_context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool ('for roadmap and backlog planning'), but it does not explicitly name alternative tools or state when not to use it. While the sibling list suggests alternatives, the description itself provides no exclusion guidance, so it earns a 4 rather than a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover idempotence and non-destructive behavior. The description adds valuable behavioral context: the change is session-scoped and becomes the default for all subsequent tool calls. This clarifies the stateful effect beyond what annotations convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The primary action and scope are front-loaded, followed by usage guidance and behavioral consequence. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter configuration tool, the description covers what the tool does, when to call it, its session-scoped behavior, and its effect on subsequent calls. The schema covers parameters, and annotations cover idempotence/safety, so nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both 'path' and 'validatePath'. The description does not add parameter-level details, but the baseline of 3 applies because the schema carries the burden adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('set') and clearly identifies the resource ('active project path') and scope ('for the current session'). It also distinguishes itself from alternatives by noting it avoids server restarts or environment variable changes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs calling at the start of a session and explains the purpose: switching between projects without restarting the server or modifying environment variables. It provides clear context but does not explicitly state when not to use it or name a sibling alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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