Konnexx Development MCP Server
OfficialServer Quality Checklist
Latest release: v1.2.2
- Disambiguation3/5
Most tools are clearly distinct, but generate_tickets and generate_tickets_batch overlap significantly in purpose, both generating tickets. Additionally, synthesize_documentation orchestrates multiple individual workflow steps, which could lead to misselection when an agent only needs a single step.
Naming Consistency4/5Tool names follow a consistent verb_noun pattern (generate_tickets, design_erd, implement_feature), with platform-specific suffixes like _web and _mobile. Minor inconsistencies include abbreviations (db_query, docs_lookup) and the slightly awkward generate_tickets_batch.
Tool Count3/5At 23 tools, the server is on the heavy side of the ideal range. While the broad scope of development workflows justifies many tools, it borders on being overwhelming and could benefit from consolidation.
Completeness4/5The tool surface covers the full development lifecycle from requirements and architecture through implementation, testing, PR creation, and package publishing. Some gaps exist (e.g., no explicit deployment or ticket update tools), but core workflows are well-covered.
Average 2.9/5 across 23 of 23 tools scored. Lowest: 1.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It doesn't state whether this reads, mutates, or creates state, whether it requires input documentation from a prior step, what side effects occur, or whether it is safe to call repeatedly. For a tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short at one clause, which could be seen as efficient, but it is under-specified rather than concise. It lacks any structural elements like usage context, output description, or examples. The brevity is more an artifact of poverty than genuine economy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a complex extraction tool with no output schema, no annotations, and no parameter documentation. The description gives no sense of what the extracted requirements look like, what documentation it consumes, whether it generates tickets downstream, or what the return value contains. Given the rich sibling ecosystem, this tool is severely under-documented.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters and schema coverage is 100% (trivially, since there are no parameters). With no parameters to document, the description doesn't need to add parameter semantics. Baseline 4 applies for zero-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5Does the description clearly state what the tool does and how it differs from similar tools?
The description says 'Extract and structure requirements from documentation' which uses a verb and resource, but it's vague about the source (which documentation?), the target output format, and scope. It doesn't distinguish from siblings like synthesize_documentation or generate_tickets, and lacks specifics on what 'structure' produces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does 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. Given siblings like synthesize_documentation, generate_tickets, and design_erd, the agent cannot determine when requirement extraction is appropriate. No exclusions, preconditions, or alternative references are given.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It doesn't state what the tool modifies, outputs, or requires as prerequisites (e.g., whether an ERD must already exist, or whether this mutates shared state). For what appears to be a workflow/project-management tool, the side effects are unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with zero wasted words. It's appropriately short for a 0-parameter tool, though it borders on under-specification given the opaque domain context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 0 params, no output schema, and no annotations, the description is the only source of information, and it's quite thin. It doesn't explain output format, side effects, or reasoning flow. For a tool in a complex multi-step workflow with 22 siblings, this is insufficient to guide correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, so the schema provides no guidance. With schema coverage at 100% (trivially, since there are no params), the baseline for parameter semantics is 4 per the rules. The description adds no param-level detail, but there are no params to document, so nothing is missing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5Does the description clearly state what the tool does and how it differs from similar tools?
The description "Specify API endpoints from requirements and ERD" names the verb and resource ('specify' + 'API endpoints') and identifies the source artifacts (requirements and ERD). However, the tool is split across many siblings in a reverse-engineering workflow, and the description doesn't distinguish it from related steps like design_erd or generate_tickets, nor does it clarify what 'specify' produces concretely (a spec doc? a file? a schema?).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool vs. alternatives. With 21 siblings in the list, it doesn't indicate whether this should be run before implement_feature, after design_erd, or in what sequence. Context must be inferred entirely from the name and surrounding workflow.
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?
No annotations are provided, so the description carries full behavioral burden. It mentions 'proper error handling' but doesn't disclose key behaviors: whether the query is read-only or allows mutations (INSERT/UPDATE/DELETE), whether there are safety restrictions, connection requirements, or limitations. The mention of 'proper error handling' is a promise, not a disclosure of 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with zero waste. Every word contributes. It's appropriately brief for a single-parameter tool, though the content could be more substantive.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool executing raw database queries, the description is notably incomplete. No output schema exists, so the description should explain what the tool returns (rows, affected counts, errors). No behavioral annotations exist. The description doesn't mention query type restrictions, timeout behavior, or whether it supports reads, writes, or both. Given the sensitivity of raw SQL execution tools, significantly more context is warranted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single 'query' parameter, and the description adds the 'standardized query execution with proper error handling' context. However, the description doesn't clarify query syntax expectations, whether parameterized/placeholders are supported, read vs. write statements, or any constraints on query format. It's a marginal incremental improvement over the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it executes a database query workflow using Database MCP, which is a specific verb+resource pairing. However, it's vague about what kind of queries are supported, what 'standardized query execution' means, and doesn't clearly distinguish from siblings (which are mostly feature/test tools, making some distinction implicit). The purpose is generally clear but under-specified.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 22 sibling tools including generate_tickets, implement_feature, and other unrelated functions, the description doesn't clarify which database scenarios this handles vs. excludes. No examples, no conditions, no alternatives mentioned.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It doesn't state whether ticket generation is idempotent, whether it overwrites existing tickets, whether it requires prerequisite plans or extracted requirements, or what the output/side effects are. For a batch operation that likely creates many artifacts at once, this is insufficient transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single, efficient sentence with zero waste. It front-loads the primary action and includes the domain scope. Not verbose, though it could potentially include a brief usage note without much cost. This is appropriately concise without being under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a batch-generation tool with no annotations and no output schema, the description is thin. It does not mention return values (e.g., ticket IDs generated), behavior on partial failure, or prerequisite conditions. Given the tool's operational nature (creating multiple tangible artifacts), the description provides insufficient context for an agent to safely invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters ('epic' and 'phases') are already documented in the schema. The description adds no additional meaning about format or constraints beyond 'phase numbers (e.g., P1, P2, P3)' already present. Baseline 3 is appropriate since the schema does the heavy lifting and the description doesn't contradict or enrich it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate multiple ticket batches for architecture projects' uses a specific verb+resource ('Generate ticket batches') and narrows scope to 'architecture projects,' distinguishing it from the singular sibling 'generate_tickets.' However, it doesn't clarify what 'multiple ticket batches' means (how they're grouped, what a batch represents) or how this relates to the singular variant, leaving some ambiguity about the tool's exact role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus 'generate_tickets.' The name suggests a batch counterpart, but the description provides zero exclusions or alternative references. For a tool with a near-identical sibling, the lack of differentiation guidance is a notable gap.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It doesn't state side effects (e.g., whether it modifies files, generates code, requires a running environment), what inputs it processes, what state changes occur, or what the output/result looks like. For an implementation tool, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short sentence with no waste. It's brief and to the point, though it could afford to be slightly longer if it added valuable detail about behavior or usage. For what it includes, it's efficiently written.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a substantive implementation tool with a single parameter and no output schema, yet the description provides minimal context. With sibling tools for web and generic implementations, the mobile-specific distinction needs elaboration. No annotations offset the thin description. The tool performs meaningful work (implementing a feature) that requires platform-specific knowledge the description doesn't convey.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning the 'ticket' parameter is documented in the schema as 'Ticket description.' The description adds the context that this is a Flutter mobile feature implementation, implying the ticket is a mobile feature request, but doesn't elaborate on ticket format, required sections, or how the ticket is processed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description "Implement a feature for Flutter mobile application" has a specific verb+target (implement feature for Flutter mobile). However, it doesn't distinguish itself from sibling tools like implement_feature, implement_feature_web, or other implement-related tools except through the platform qualifier. The scope of what counts as 'implementing a feature' is undefined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings. The description doesn't mention prerequisites like needing a ticket first, whether implementation involves code generation, testing, or what distinguishes mobile Flutter implementation from its web counterpart or from the generic implement_feature. There's no when/when-not guidance at all.
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?
No annotations are provided, so the description carries full behavioral disclosure burden. It discloses that operation is non-deterministic/parallel ('using parallel agents') which is useful, but fails to disclose what happens on failure—whether partial fixes are committed, whether the repo is left in a modified state, cleanup behavior, or reversibility. 'Fix them' implies mutation of workspace files with no caution about state changes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single concise sentence with no filler words. It front-loads the verb ('Run tests') and states the action clearly. It's efficiently written; the only issue is that brevity is achieved by omitting useful context rather than by trimming redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a complex mutation tool (runs tests, modifies code) with no annotations and no output schema. With many closely-related siblings (test_fix_incremental, test_fix_web, test_fix_incremental_web), the description needs to clarify scope, platform, and relationship to siblings. It does none of this. The single sentence is adequate for a trivial tool but insufficient for a tool of this complexity and sibling density.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There is only 1 parameter (spec) with 100% schema description coverage, and the description doesn't mention the parameter at all. However, the schema itself fully documents the spec levels and their meanings (low=4 cores, default=6-8, high=12+), so the description adds nothing but also doesn't need to—the schema carries the full weight. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb+object (run tests, fix failures) but is somewhat vague on mechanism. 'Using parallel agents' gives a hint of execution model. However, among ~10 sibling tools including test_fix_incremental, test_fix_web, test_fix_incremental_web, there is zero differentiation—no mention of scope, platform, or whether this is the base/general variant vs the incremental/web versions. The purpose is understandable but not distinguishing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use guidance is provided. With siblings like test_fix_incremental (presumably incremental fixing), test_fix_web, and test_fix_mobile, an agent gets no indication of which tool to select. The description offers no context about when this base test_fix is preferred over its specialized siblings, no exclusions, and no alternatives mentioned.
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?
No annotations are provided, so the description carries the full burden. 'Fixing failures as they occur' implies the tool mutates code (potentially dangerous — modifies source files). It doesn't disclose what gets modified, whether changes are reversible, whether it commits, or whether it's a read-only test runner that suggests fixes vs actually applying fixes. The mutating behavior is under-disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, efficient, no wasted words. The sentence is compact and front-loaded with the core action. However it could benefit from being slightly longer to add usage guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation-capable tool with no annotations and no output schema, the description is thin. It doesn't state what happens on failure (stops, continues, reports), how long it runs, what files it touches, or whether the spec param affects behavior. Given the complexity implied by 'fixing failures' and zero annotation coverage, more behavioral disclosure is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% — the single 'spec' parameter is fully documented in the schema with enum values (low/default/high) and a description. The tool description adds nothing about the param beyond what the schema states, which warrants the baseline 3. It doesn't clarify what each spec level means in terms of test coverage or resource usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it runs tests incrementally for Next.js and fixes failures. It has a specific verb+resource+context (Next.js web app). However, it doesn't distinguish from siblings like test_fix, test_fix_incremental, or test_fix_web — 'incremental' and 'web' hints at the distinction but the description doesn't clarify what makes this tool unique vs test_fix_web or test_fix_incremental.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this vs test_fix, test_fix_incremental, test_fix_web, or test_package. There are 23 sibling tools with overlapping concerns (implement_feature_web, test_fix_web, test_fix_incremental). The description gives no context about when this is appropriate — e.g., during development cycle, for CI, or for which repo/workspace context.
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?
No annotations are provided, so the description carries the full burden. It doesn't disclose whether this makes external network calls, whether it can fail when libraries aren't indexed, what happens with queries that have no matches, or whether it modifies any state. The external dependency on Context7 MCP is mentioned but without behavioral caveats.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clean sentence that states the tool's purpose and value proposition efficiently. It's front-loaded and has no wasted words. Could arguably be improved by adding usage context, but as written it's concise and focused.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter lookup tool with no output schema and no annotations, the description provides the core purpose and what type of content to expect (up-to-date library documentation and code examples). It doesn't detail return format, failure modes, or common usage patterns, but for a relatively simple lookup tool targeting a well-known MCP server, this is in the acceptable range.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with only one parameter (query). The description provides no additional meaning beyond what the schema declares—it doesn't explain query format preferences, complexity expectations, or how to phrase effective queries. However, with a single self-explanatory parameter and full schema coverage, the baseline of 3 is appropriate since the schema already documents everything.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool executes a 'documentation lookup workflow using Context7 MCP' and provides 'up-to-date library documentation and code examples.' It has a clear verb (execute lookup) and resource (Context7 docs), though 'workflow' is somewhat vague and it doesn't distinguish itself from sibling tools like synthesize_documentation which might sound related despite covering different functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It doesn't state when NOT to use it, doesn't mention that synthesize_documentation might be a better fit for generating docs vs. looking them up, and provides no context about when documentation lookup is appropriate in the broader workflow.
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?
No annotations are provided, so the description carries full burden for behavioral disclosure. It says it 'clears' files (a destructive action) and claims to follow team standards, but doesn't state what gets destroyed, whether the action is reversible, what 'plan files' specifically are, or what the side effects are. For a destructive cleanup operation with zero annotation coverage, this is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no filler or redundancy. The description is appropriately short for a zero-parameter tool. However, the phrase 'Follows team standards for cleanup' is arguably boilerplate that adds little specific value, slightly reducing the conciseness score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a destructive operation (clearing/deleting files) with no annotations, no output schema, and minimal behavioral description. It doesn't explain what files would be affected, whether it's safe for the agent to run unbidden, what happens on success/failure, or what 'plan files' are. For a tool that permanently deletes project content, the description is under-specified and should include safety/reversibility context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema coverage, the schema leaves nothing to document. The description references 'Cursor plan files' and 'team standards' which adds some operational context, though it's thin. Since there are no parameters to explain, the baseline of 4 is appropriate — there's nothing missing in parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb+resource: 'automatically clear Cursor plan files from the project.' It identifies what the tool does clearly enough. However, it doesn't distinguish this from siblings well — the sibling list is development/task-oriented tools, and it's unclear how clearing plan files fits into that workflow. The purpose is clear but the broader role (system maintenance vs project work) is ambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There's no when-to-use guidance, no mention of alternatives, and no context about when this cleanup should be triggered. 'Follows team standards for cleanup' is vague and offers no practical guidance about when an agent should invoke this versus other operations. The description implies a cleanup/maintenance role but never states when this is appropriate.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description doesn't state what 'requirements' means here, whether this is a read-only design generation or mutates state, whether it persists anything, or what artifacts are produced. There's no disclosure of side effects or outputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, zero waste, gets the point across. Not overly verbose. However, this brevity might be concealing the absence of important usage context rather than being efficient with rich information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description must carry full context. With zero parameters, the description is the only thing the agent has to work with. It identifies the core function but lacks context about what triggers this design step, what input format requirements take, or what the resulting diagram is used for downstream.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, so the parameter semantics burden is minimal. The description mentions the input source ('from requirements') which provides the only context needed. With no parameters, the baseline is 4, and the description adequately conveys that requirements are the implicit input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Design Entity-Relationship Diagram from requirements' uses a specific verb (Design) and resource (Entity-Relationship Diagram) plus the source (requirements). It's clear about the core purpose, though it doesn't distinguish from siblings like specify_api_endpoints or extract_requirements in terms of when ERD design fits into the workflow.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. Given siblings like extract_requirements and specify_api_endpoints exist, there's no clarification about whether this should be used before/after those, or what kind of requirements are expected as input. The precedence relationship to other design tools is entirely absent.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not state whether this is a read-only aggregation tool or one that mutates state (e.g., writes files, creates artifacts). 'Orchestrate complete architecture workflow' strongly implies it may call other tools or perform multiple side effects, but the description doesn't disclose what gets changed, what's created, 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence with no wasted words. It's appropriately brief given the zero-parameter schema. However, the brevity comes at the cost of clarity—it packs two ambitious verbs ('orchestrate' and 'synthesize') into one phrase without elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having zero parameters and no output schema, the description is insufficient for a tool that 'orchestrates a complete workflow.' A tool of this complexity—likely chaining multiple steps—needs to explain what the workflow comprises, what documentation is generated, where outputs go, and what the agent should expect. The description just names the orchestration without explaining the orchestration.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0 parameters, so the baseline is 4 per the rubric. There are no parameter semantics issues to compensate for since the tool takes no input. The description doesn't need to explain any parameter meaning because none exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Orchestrate complete architecture workflow and synthesize all documentation' uses a clear verb ('orchestrate', 'synthesize') and names the resource (architecture workflow, documentation). However, it's quite abstract and doesn't specify what the orchestration actually does step-by-step, what documentation is produced, or what the end state looks like. It distinguishes somewhat from siblings like design_erd and architecture_review but the purpose is vague about the actual actions taken.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 like architecture_review or design_erd. The description does not mention prerequisites (e.g., must have requirements extracted first), nor does it explain what this tool does that the other architecture-related tools don't. An agent would have difficulty deciding between synthesize_documentation and architecture_review.
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?
With no annotations provided, the description carries full burden of behavioral disclosure. It states the tool reviews for architectural compliance but doesn't disclose what it does with findings, whether it modifies files, what the output format is (report? commit?), or whether it requires prior setup. For what appears to be an analysis/review tool, the side-effect profile is unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence) but the 'architecture' verb+resource lacks clarity about architectural domains. It's efficient but borderline under-specified, sitting between genuine conciseness and merely brief. The sentence is front-loaded with the action, but the parenthetical could be expanded to add value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a 0-parameter tool, no output schema, and no annotations, the description is the sole semantic carrier. It's unclear what 'code' refers to (all repository code? staged changes?), how findings are delivered, or what the compliance review process entails. Given the tool complexity (an architectural review presumably produces significant output), this is under-specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are 0 parameters, and schema coverage is 100% (vacuously, with an empty schema). With no parameters, the description doesn't need to explain parameter semantics, and the baseline of 4 applies. The tool takes no explicit inputs, which is a relevant fact the description's sparse context indirectly conveys.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (Review) and resource (code) with a specific purpose (architectural compliance for DDD, Laravel patterns). It distinguishes from siblings like architecture_review_web which suggests a different platform target, though it doesn't explicitly differentiate. The parenthetical makes the scope reasonably clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 like architecture_review_web or when architecture review is appropriate in the workflow. The description implies it's the general/desktop variant but doesn't say when to choose this over architecture_review_web. No exclusions or prerequisites are mentioned.
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?
No annotations are provided, so the description carries full burden of behavioral disclosure. It doesn't state whether this is a read-only rendering operation or a mutating/generating one, what files it creates or modifies, whether it persists artifacts, or what side effects it has. For a chart-generating tool, the lack of disclosure about output format (embedded HTML, image file, markdown) is a gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with the actionable verb 'Create', wastes no words. Efficient and direct. Could arguably be considered under-specified rather than concise, but the sentence structure itself is clean.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description is fairly minimal. It tells what it creates and from which inputs. However, it doesn't describe the output artifact details, whether a diagram is persisted/rendered, or how this fits the overall generation pipeline. Given the tool has no schema or annotations to lean on, the description could reasonably add more.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters and 100% schema coverage, meaning everything is derived from existing context (tickets/endpoints). The description does clarify the input source (tickets and API endpoints), which adds meaning. Since there are no parameters to document, this dimension is a neutral 3 - the description's clarification that it pulls from existing tickets and endpoints is helpful but minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb+resource ('Create timeline and Gantt chart') and names the input source ('from tickets and API endpoints'). It distinguishes the artifact type (timeline/Gantt chart) from siblings like design_erd or specify_api_endpoints, though it doesn't explicitly mention generating from already-created tickets vs creating them, nor clarify what output it produces (file, diagram, page).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. It doesn't state whether tickets and API endpoints must already exist, what order in the pipeline it belongs, or when to prefer analyze/design tools instead. No prerequisites, exclusions, or alternative tool references given.
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?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. The description states tickets are generated 'in batches of 5', which is a behavior, but it doesn't disclose whether this is a state-mutating operation (creating actual ticket records), whether it requires authentication or permissions, the side effects of generation, or what the output format will be. For a generative operation with unclear side effects, this is 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, tight sentence that conveys the core action, scope, and input source without padding. It's front-loaded with the primary action. No redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, no annotations, and sits among a large sibling family with overlapping functions (generate_tickets_batch, implement_feature, specify_api_endpoints). The description is too thin to fully orient an agent: it doesn't explain the pipeline position (what must exist before this runs), what the generated tickets represent, or how batches of 5 relate to the phase/epic parameters. For a multi-step workflow tool in a crowded sibling set, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters (epic and phase) are documented in the schema. The description mentions the tools consumes 'API endpoints and timeline' as inputs, which adds source context that maps to the epic/phase parameters conceptually, but it doesn't add format details or clarify how the parameters influence ticket generation. Baseline 3 is appropriate given full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (generate), the resource (development tickets), the batch size (5), and the input source (API endpoints and timeline). It uses a specific verb+resource construction that distinguishes purpose. However, it doesn't explicitly distinguish itself from the sibling 'generate_tickets_batch' tool, which is a notable gap since batch generation is the core of this tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use guidance is provided. The description doesn't clarify when to use this tool vs. 'generate_tickets_batch' (which appears to be a sibling that also generates tickets). It also doesn't specify prerequisites like having completed specify_api_endpoints or create_timeline_gantt first, which the name 'from API endpoints and timeline' implies but doesn't state 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?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Fix failures' is ambiguous — it's unclear whether the tool autonomously modifies code, requires approval, or only suggests fixes. For a tool that both tests AND fixes (a potentially mutating action), there's no disclosure about what gets modified, whether changes are automatically applied, or any failure handling behavior. This is a significant gap for a tool with destructive implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It conveys the core purpose compactly. However, it's slightly under-specified given the mutating 'fix' action, but brevity isn't the issue — completeness is.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that performs both testing and code-fixing (a mutating operation), the description is too thin. There's no output schema, no annotations, and no explanation of what 'fix failures' entails (scope of fixes, safety, reversibility). Given the number of sibling test/fix tools, more context about which scenarios warrant this specific tool would be valuable. The description is adequate as a label but incomplete as operational guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the single 'spec' parameter is fully documented in the schema with its enum values and description. The description adds the domain context (that the spec relates to machine specifications, implicitly). Baseline 3 is appropriate since the schema handles parameter documentation and the description adds marginal connection to the Next.js context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('Run tests') and resource ('Next.js application') with an explicit action ('fix failures'). It identifies the tool as a combined test-and-fix workflow. Distinguishes itself from siblings like test_fix (non-web variant) and test_fix_incremental via the 'Next.js application' scoping and failure-fixing focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 like test_fix, test_fix_incremental, or test_fix_incremental_web. The sibling set has several test/fix variants, and the description provides no criteria for choosing among them (e.g., when incremental is preferred, when to use non-web variants). Users must guess whether 'fix failures' means auto-fixing or only reporting.
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?
No annotations are provided, so the description carries full burden of behavioral disclosure. It does not state whether the tool is read-only or mutates files, whether it fixes issues automatically or just reports them, whether it requires existing code to be present, or what it does with findings. For an analysis-type tool, the lack of clarity on whether it reports or fixes is a notable gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that communicates the core purpose with no waste. It bundles the verb, resource, and platform context efficiently. However, given the tiny length, it could have included more behavioral context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 0 parameters and no output schema, the tool's simplicity does not fully excuse the sparse description. Given the web-specific naming and the existence of a sibling 'architecture_review', the description should clarify the distinction, the workflow position (e.g., run after implement_feature_web), and expected outputs. The sibling naming suggests possible duplication that isn't disambiguated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, so there are no parameter semantics to document. The schema is empty and the description is not required to compensate for undocumented parameters since none exist. The baseline of 4 for zero-parameter tools applies, though the description could have explained what codebase it operates on.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool reviews code for architectural compliance with Next.js patterns, using a specific verb (review) and resource (code compliance). It distinguishes itself from the sibling 'architecture_review' through the '(Next.js patterns)' qualifier, making the web-specific scope clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus the sibling 'architecture_review' or 'implement_feature_web'. The description doesn't clarify the expected workflow (e.g., whether it should precede commit_pr or follow implementation), nor does it state any prerequisites. The Next.js qualifier implies use for web projects but this is implied rather than explicit.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions a '7-step workflow' (Types, Service, Hooks, Components, Screens, Routes) which gives some flow transparency, but it doesn't disclose side effects: whether this mutates code, creates files, requires commit permissions, modifies the git history, or what the impact is on the existing codebase. For a mutating implementation tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact — two sentences. The first sentence explains the workflow steps concisely, the second gives a strong usage directive. No wasted words, though it could be improved by front-loading the core action even more explicitly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that appears to perform substantial code generation and file modification, the description is minimal given the tool's complexity. There's no output schema so the description should explain what a successful implementation produces (files created, patterns followed), and there's no mention of failure modes or rollback behavior. The 7-step workflow naming is helpful but doesn't cover post-execution state or what the agent should verify after calling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'ticket' described as 'Ticket description'. The description adds workflow context (how the ticket flows through the 7 steps) which is beneficial. However, the description doesn't add syntax or format specifics for the ticket beyond what the schema provides — the schema already describes it as a 'Ticket description' string. The value-add here is the workflow context rather than parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it executes a Next.js feature implementation workflow and names the 7-step process, giving clear verb+resource. However, it does not distinguish itself from the sibling 'implement_feature' tool, which appears to be the general-purpose version without the '_web' suffix. The purpose is clear about what it does but ambiguous about how it differs from its sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'ALWAYS use this for Next.js features' which provides a strong usage directive and implies this is the canonical tool for the platform. However, it doesn't explicitly state when NOT to use it or name alternatives (like when to use implement_feature_mobile or the base implement_feature), leaving the exclusion boundaries implicit.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description doesn't clarify what 'fixing failures' means operationally — does it modify source code? regenerate tests? How does the incremental behavior manifest (does it persist state between runs)? For a tool that auto-fixes tests, this behavioral ambiguity is a notable gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with the main purpose. No wasted words. It's appropriately sized for a tool of this complexity; the description clearly communicates the core value proposition without padding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an auto-fixing test tool with no annotations and no output schema, the description should provide more context about side effects (does it commit changes? modify files?), failure handling, and what 'incrementally' means operationally. Without these details and with no annotations, the agent has incomplete information about a tool that mutates state.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the single param 'spec' is fully described with enum values and meanings in the schema, so the description doesn't need to compensate. The description adds nothing about params, but baseline 3 is appropriate given full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb ('Run tests') and the resource ('incrementally, fixing failures as they occur'), and it distinguishes from the sibling 'test_fix' by noting the incremental approach and speed advantage ('faster for large test suites'). It's clear but doesn't explicitly differentiate from 'test_fix' other than implying the incremental strategy.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it ('faster for large test suites') which serves as a usage hint, but it doesn't give explicit when-not-to-use guidance or name alternative tools like 'test_fix' for smaller suites. The guidance is implied rather than explicit.
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?
No annotations are provided, so the description carries the full burden. The description mentions it 'executes' a full workflow and 'uses MCP servers,' which implies side effects (planning, code changes, testing), but doesn't disclose: whether this creates/modifies files, whether it requires authentication, whether it's a long-running multi-step tool, whether it spawns sub-operations, or what risks/destruction it may cause. For a workflow-orchestrating tool with no annotations, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact at two sentences and includes the workflow steps compactly. The 'ALWAYS use this' imperative is useful but could be slightly trimmed. The MCP server list adds useful context without bloat. Overall efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a complex multi-stage orchestration tool with no output schema and no annotations. The description covers the workflow stages and team patterns, but lacks details about: what the agent should expect back/see during the process, how the plan→approve stage works (does the agent need to confirm/approve interactively?), time expectations, or what happens on failure mid-workflow. Some critical operational semantics are missing 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.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters (ticket and architecture_report). The description adds the context that the ticket drives the whole workflow, but doesn't elaborate on what formats are expected for ticket IDs vs descriptions, or how the optional architecture_report influences behavior. Baseline 3 is appropriate given full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb+resource: 'Execute complete feature implementation workflow' with specific stages (plan → approve → implement → review → test). It distinguishes from siblings like test_fix, architecture_review, and the web/mobile variants by describing the full integrated workflow. However, it doesn't explicitly differentiate from implement_feature_web or implement_feature_mobile, which may be platform-specific variants.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage guidance: 'ALWAYS use this for feature implementation to ensure consistency with team patterns.' It names the MCP servers used (GitHub, Database, Context7). However, it doesn't explicitly state when NOT to use this tool or what alternatives exist for platform-specific implementations (web/mobile variants suggest some distinction is needed).
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?
There are no annotations, so the description carries full burden for behavioral disclosure. The description says it 'executes a workflow' and 'diagnoses issues' but doesn't disclose what the workflow actually does, whether it performs mutations (like running tests that could fail), what side effects occur, or what constitutes 'success.' For a 0-parameter tool that runs a multi-server verification, this is thin behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences—the first states the purpose and scope, the second clarifies usage intent. It's efficient with zero filler words. It could arguably be even more explicit about diagnostic behavior, but structurally it's tight and front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 0-parameter, no-output-schema tool, the description does a reasonable job. It names the five servers being verified, which is genuinely useful. The main gap is that the description doesn't suggest what output or actions an agent should expect after invocation (e.g., what diagnose results might look like), but given the tool's simplicity, this is minor.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters and 100% schema coverage (trivially, as there are no parameters). With no parameters to document, the baseline is 4. The description appropriately doesn't waste space inventing parameter documentation, and the listed servers provide context about scope.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb (verify/execute workflow), the resource (MCP servers), and enumerates the specific servers (Context7, GitHub, Filesystem, Database, Browser). It distinctly names the testing/diagnosis purpose, differentiating it from the sibling tools which are all about tickets, ERDs, requirements, implementation, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states when to use it ('test MCP connectivity and diagnose issues') which gives clear context. However, it does not explicitly exclude alternatives or note when not to use it. The siblings are semantically very different so the contrast is implicit, but there's no explicit when/not 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 provided, so the description carries the full burden. It does disclose the full sequence of side effects (git commit, tag, push, npm publish), which is good. However, it doesn't disclose that the 0-parameter tool will infer package/version from context or conventions, and doesn't mention failure modes, rollback options, or authentication requirements for npm/GitHub.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the workflow steps. Slightly dense with the step enumeration but all are relevant. The 'ALWAYS use this' directive adds clear emphasis for the AGENT. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists the full workflow steps which helps the agent understand scope. However, given this is a complex multi-step publishing operation with no output schema and no annotations, it could benefit from disclosing what the return value looks like or what happens if the git commit fails mid-pipeline (partial state). The description covers the 'what' but not the 'what if'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, so there's no schema to compensate for. The description compensates by explaining what the tool does internally without requiring inputs. With 0 params and 100% schema coverage, baseline is 4, and the description aligns with this.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool executes a complete package publishing workflow with specific verb+resource (publish_package) and lists concrete steps: reviews changes, version bump, builds, updates version, git commit/tag, push, npm publish. However, it doesn't distinguish itself from sibling tools like test_package or commit_pr, though its scope is fairly unique (publishing).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'ALWAYS use this for publishing konnexx-dev-mcp' which provides strong when-to-use guidance specific to this package. It doesn't provide when-not-to-use or alternative tools, but given the tool's specialized purpose, the context is reasonably clear.
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?
With no annotations provided, the description carries full burden for behavioral disclosure. It details the side effects (builds, creates npm link) which are meaningful transactional behaviors. However, it doesn't disclose potential destructive effects (e.g., does npm link overwrite existing links?) or cleanup behavior. The described side effects are substantive for this category.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, first sentence front-loads the action with concrete step enumeration, second adds usage context. It's efficient with no wasted words, though slightly dense in the first sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 0-param, no-output-schema tool, the description adequately covers the operational behavior (build, link, verify startup, validate files) and the specific package targeted. The step enumeration gives the agent a clear mental model of what execution entails. It could add failure-mode expectations but is largely complete for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters and 100% schema coverage (empty schema is fully described). With no parameters, the description's job is to describe workflow behavior, which it does thoroughly by enumerating the steps. There's no parameter ambiguity to resolve. Baseline 4 applies for zero-param tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('execute local package testing workflow') and the specific resource (konnexx-dev-mcp package). It enumerates the concrete steps (builds package, creates npm link, verifies server startup, validates command files), which distinguishes it from siblings like publish_package and verify_mcp_servers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context: 'test the konnexx-dev-mcp package locally before publishing.' This implies it's a pre-publish step, but it doesn't explicitly state when NOT to use it or name alternatives. Given the sibling verify_mcp_servers (which is narrower), explicit exclusion would strengthen this dimension.
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 provided, so the description carries the burden. It discloses that the tool modifies the repository state (commits, pushes, cleans up plan files) and depends on GitHub MCP being available. However, it doesn't disclose side effects like what happens to plan files specifically, whether the push is force or normal, or what happens if GitHub MCP is unavailable. The multi-step destructive behavior is partially disclosed but not fully.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a compact two-sentence block that covers purpose, scope, dependencies, and usage preference. It's front-loaded with the primary action and includes the critical 'ALWAYS use this' guidance. Slightly verbose in listing every step, but each is relevant for setting expectations of a multi-step workflow.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, no-output-schema tool, the description is quite complete. It lists the full workflow steps, mentions dependency on GitHub MCP, and provides a usage directive. It could note failure modes (e.g., what happens if no changes to commit) but given the simplicity of the interface, this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, so there's nothing to document. With no parameters and 100% schema coverage (trivially true with zero params), the baseline for 0 params is 4. The description compensates by explaining what the tool does internally, which gives the agent context on what to expect.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states what the tool does: executes a complete commit and PR workflow including detecting project type, generating conventional commit messages, cleaning up plan files, committing, pushing, and creating a PR. It uses a specific verb ('Execute') with a clear resource (commit and PR workflow). It doesn't explicitly distinguish from siblings but the workflow is specific enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides excellent usage guidance: 'ALWAYS use this instead of manual git commands to ensure team standards.' This is an explicit directive on when to use this tool versus the alternative (manual git commands), making it clear this is the preferred path for commits and PRs. This is strong guidance for an agent.
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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