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vjrivmon

Smart Agent Workflow MCP

by vjrivmon
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Server Quality Checklist

67%
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  • Latest release: v0.6.1

  • Disambiguation3/5

    Several tools overlap in scope: abort_worktree, rollback_feature, and cleanup_worktree all handle worktree termination at different levels, while create_worktree and start_feature both create worktrees. The descriptions help clarify the hierarchy, but an agent may struggle to choose between low-level and high-level equivalents.

    Naming Consistency4/5

    Most tools follow a consistent verb_noun snake_case pattern (e.g., start_feature, verify_build, save_context). The exception is 'worktree_status', which is a noun phrase rather than a verb-led command, making it slightly inconsistent with the rest.

    Tool Count3/5

    At 20 tools, the server is on the heavier side of the typical range. While each tool has a distinct role, some are redundant due to nested operations (e.g., abort_worktree vs. rollback_feature), suggesting the count could be trimmed without losing functionality.

    Completeness4/5

    The tool surface covers the full feature development lifecycle—start, test, build, merge, rollback, and cleanup—plus memory/context management and documentation. Minor gaps exist, such as no direct way to list completed features or delete specific memories, but these are easily worked around.

  • Average 3.8/5 across 20 of 20 tools scored. Lowest: 2.9/5.

    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.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?

    Without annotations, the description must disclose behavior itself. It only says 'Gets the current status' but does not mention that the tool by default returns a limited number (limit default 10) or that 'all active workflows' may be constrained by this limit. It also does not mention the inclusion of historical data via 'include_history', the return format, or side effects. This under-disclosure could mislead an agent about the tool's default 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 immediately states the primary function. It is front-loaded and easy to scan. However, it is slightly too sparse, missing key details about the 'active' vs 'historical' scope, but this is more of a completeness issue than a conciseness one.

    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 and no annotations, the description needed to provide more context about return values, default behavior, and the meaning of 'active' versus 'history'. The description does not explain what the tool returns in terms of structure, nor does it clarify the relationship between 'active workflows' and the 'limit' parameter. This leaves significant gaps for an agent trying to use the tool 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 coverage is 100%, with both 'limit' and 'include_history' having clear descriptions in the schema. The tool description adds no additional parameter context, but since the schema is fully documented, the baseline of 3 is appropriate. No further elaboration is needed.

    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 gets the current status of workflows and lists what it includes (phase, steps, progress). It is distinct from sibling tools like 'worktree_status' or 'get_test_results'. However, there is slight ambiguity since the description says 'active workflows' while the schema mentions 'historical workflows' and an option to include history, so the scope is not perfectly aligned.

    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 like 'worktree_status' or 'get_test_results'. There are no explicit use cases, preconditions, or exclusions. The only implied context is that it's for workflow status, but sibling differentiation is 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 only says 'ephemeral' without explaining what that entails—e.g., whether it creates a new branch, checks out the worktree, or requires cleanup. Side effects and lifecycle are undisclosed.

    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, immediately front-loaded with the verb and resource. It contains zero unnecessary words and delivers a concise, clear statement of 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?

    The tool has 2 parameters, no output schema, and no annotations, so the description must compensate. It fails to explain the worktree lifecycle, naming conventions, or the relationship to the 'task' parameter. For a side-effect-rich tool like git worktree creation, this is insufficient context.

    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% for both parameters. The description adds no param-specific meaning beyond stating the purpose. The baseline of 3 is appropriate since the schema already documents task and base_branch with defaults.

    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 verb 'creates', the resource 'git worktree', and the purpose 'isolated feature development'. It distinguishes the tool from siblings like abort_worktree and cleanup_worktree by focusing on creation and ephemerality.

    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 usage for feature development but provides no explicit guidance on when to use this tool versus alternatives. There is no mention of prerequisites, when not to use it, or how it relates to sibling tools like start_feature or worktree_status.

    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, and the description offers little behavioral detail beyond the obvious execution of tests. It mentions 'Supports retries and custom test paths,' which paraphrases schema parameters rather than revealing side effects, failure behavior, or output.

    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 two sentences and gets to the point quickly. The first sentence identifies the core function; the second adds policy context and feature support, but is not 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?

    Given the lack of annotations and output schema, the description should explain what happens after running tests, such as exit codes or failure effects. It only states the tests must pass, leaving uncertainty about output and 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 coverage is 100%, so baseline is 3. The description's mention of retries and custom test paths adds no new semantic meaning since the schema already documents retries and test_path.

    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 'Runs E2E tests with Playwright,' using a specific verb and resource. It is distinct from siblings like generate_test_template or get_test_results by focusing on execution rather than creation or retrieval.

    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 'Tests MUST pass before merge' provides clear context for when this tool should be used—before merging changes. However, it does not explicitly name alternatives or exclusions, so it stops short of full 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?

    With no annotations provided, the description carries the full burden for behavioral disclosure. It does not state whether the tool writes a file to disk, returns the template as output, or if it requires a specific working directory. The side effect of generating a template is implied but not clarified, and the policy sentence adds no behavioral information.

    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—two sentences that front-load the purpose and add a relevant policy. Every word earns its place, with no redundancy or fluff.

    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?

    Without an output schema, the description should clarify what the tool actually produces (a template string? a file? a path?). It also does not mention whether it requires a worktree or how it interacts with existing files. For a four-parameter tool with no annotations, this is a significant completeness gap.

    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 describes all four parameters with clear descriptions and defaults, achieving 100% coverage. The description itself adds no additional parameter-specific meaning beyond the schema, so a 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 a specific verb and resource: 'Generates a Playwright E2E test template for a feature.' This distinguishes it from sibling tools like run_e2e_tests or get_test_results, which execute or retrieve tests rather than create templates.

    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 policy 'Every feature MUST have tests before merge' gives a clear context for when to use this tool—when a feature is ready to be tested before merge. However, it does not explicitly mention when not to use it or name alternatives, though the sibling context makes the distinction fairly clear.

    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, the description must carry the full burden of behavioral disclosure. It does mention BLOCKS on failure and cleanup, but it claims 'quality gates cannot be bypassed' while the schema exposes a skip_tests parameter that explicitly allows bypassing tests (albeit with confirmation). This is misleading and under-discloses the risky escape hatch and cleanup 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 concise and front-loaded: the first sentence states the action and steps, the second provides a behavioral caveat. No wasted words, with clear prioritization of critical 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?

    For a tool with this complexity, the description covers main steps and safety, but it omits the skip_tests parameter and any mention of return values or post-conditions. It is adequate for basic use, but the missing 'dangerous' parameter and lack of output info leave 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?

    The schema already describes all three parameters with 100% coverage, so the description adds little beyond high-level actions. It references worktree and merge, but does not explain parameter semantics beyond the schema. 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 the tool's function with a specific verb ('Completes') and a resource ('a feature'), then enumerates the steps: runs E2E tests, verifies build, merges to main, cleans up worktree. It distinguishes itself from sibling tools like abort_worktree or rollback_feature by emphasizing that it is the safe merge path.

    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 this tool ('This is the safe way to merge') and implies that it should be used when quality gates are desired, unlike potentially unsafe alternatives. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a 5.

    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, the description carries full responsibility for behavioral disclosure. It says 'retrieves' which implies read-only, but the name 'restore' might imply state modification. It does not clarify whether current context is overwritten, whether permissions are required, or what happens when no workflow_id is specified. This ambiguity 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.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is two sentences long, efficiently front-loaded with the main purpose and followed by a clear usage directive. Every word earns its place with no fluff or repetition.

    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 no output schema, no annotations, and multiple optional parameters. The description explains what is retrieved and when to use it, but does not describe the return format, behavior when no workflow_id is given, or whether the restore modifies current state. This leaves notable gaps for a resume-work 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 input schema already provides complete descriptions for all four parameters (100% coverage). The tool description adds no additional parameter-level detail beyond what the schema offers, so a 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 restores context from a previous workflow and specifies the contents (decisions, learnings, files modified, related memories). This distinguishes it from siblings like save_context and checkpoint_context, which focus on saving or checkpointing rather than restoring.

    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 to resume work on a feature or learn from past implementations,' giving clear context for when to use the tool. It does not specify when not to use it or list alternative tools, but the primary use case is well-defined.

    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 states it updates files but does not mention what changes are made to existing content (e.g., append vs. replace is only in the schema), whether changes are reversible, or any permission requirements. For a mutation 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.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is two sentences with no fluff. It front-loads the primary action and target, then adds capability details and utility, earning every word's place.

    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 5 optional parameters and no output schema, and the description covers the main behavior and auto-detection features. However, it omits details about return values, failure modes, or side effects, which for a mutating operation without annotations leaves the description incomplete for full agent decision-making.

    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?

    Schema coverage is 100% for parameters, so baseline is 3. The description adds meaning beyond the schema by explaining auto-detection of sections and files, and by tying the tool to the 'current workflow,' which clarifies the role of section, doc_path, and workflow_id parameters beyond their schema descriptions.

    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 the specific verb 'Updates' and names the exact resources (CLAUDE.md, README.md), making it clear what the tool operates on. This distinguishes it from sibling tools like sync_changelog which target changelogs, and generate_completion_report which generates reports.

    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 general use case ('useful for keeping docs in sync with development') but does not explicitly state when to use this tool over alternatives, nor does it give exclusions or prerequisites. It implies usage context but lacks direct comparison to 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?

    With no annotations provided, the description carries the full burden. It discloses the output fields and the checkpoint recommendation behavior, but does not explicitly state that it is a read-only operation or mention any side effects, rate limits, or performance implications.

    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 core purpose and enumerating the metrics. The second sentence adds actionable usage context without extraneous detail. Every word 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 simple read-only tool with one optional parameter and no output schema, the description covers the key metrics and use case adequately. It doesn't detail return format, but listing the metrics is sufficient, and it doesn't need to explain sibling distinctions.

    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% description coverage for the single optional boolean parameter, fully explaining its meaning and default. The tool description does not mention the parameter, but the schema does the heavy lifting, 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.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description uses a specific verb 'Get' with a clear resource 'context health metrics' and enumerates the exact metrics returned (health score, operations count, estimated tokens, session duration, checkpoint recommendation). It is clear but does not explicitly distinguish itself from sibling tools like get_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 directly states its intended use: 'Use this to monitor context usage and anticipate compaction.' This gives clear context on when to use the tool, though it lacks explicit when-not-to-use guidance or mentions of 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?

    No annotations are provided, so the description carries the burden. It implies a read-only operation via 'Gets' and adds context about the testing gate, but it does not disclose potential side effects, limitations (e.g., no results handling), or whether any state changes occur. For a simple getter, 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?

    Two concise sentences, no fluff. The first sentence states the core action and resource, the second explains the key outcome. Every word 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 simple read tool with no output schema and no annotations, the description covers the essential purpose and the concept of a 'testing gate.' It does not detail return values or edge cases, but it is sufficiently complete for an agent to understand what the tool does and when to call 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 baseline is 3. The description adds minimal parameter-related meaning; it references 'worktree' but does not elaborate on include_output or any formatting/behavior. It does not compensate 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 uses a specific verb 'Gets' with a clear resource: 'latest test and build results from a worktree.' It also adds outcome context ('Shows if the testing gate has been passed'), which distinguishes it from sibling tools like run_e2e_tests (which runs tests) and get_workflow_status (broader status).

    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 is implied: use this to check test/build results and gate status. However, there is no explicit when-to-use or when-not-to-use guidance, nor any comparison to alternatives like verify_build or get_workflow_status. The context is clear but not explicitly contrasted with siblings.

    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, description must disclose side effects and failure modes. It only says it validates output and must succeed, but does not explain what validation entails, potential file modifications, or return 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?

    Two concise sentences that are front-loaded and contain no wasted words.

    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 simplicity and 100% schema coverage, the description adequately covers purpose and merge-gate context, though it omits return value 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?

    Schema covers 100% of parameters, so baseline is 3. Description adds no parameter-specific info but doesn't need to.

    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?

    Clearly states it runs npm build and validates output, with specific context that build must succeed before merge. Distinguishes from sibling tools like run_e2e_tests by focusing on build validation.

    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?

    Implies usage as a merge gate with 'Build MUST succeed before merge,' providing clear context. However, no explicit alternatives or exclusions are mentioned.

    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 no annotations provided, the description carries the full burden. It discloses the output format (markdown), the content included, and the save location, but does not mention behaviors like whether existing reports are overwritten, whether it requires a workflow_id, or what happens if the workflow is not complete. The provided info is useful but incomplete for full behavioral 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 two sentences long, front-loaded with the primary purpose, and every sentence adds value. It efficiently conveys what the tool does, what it includes, and where it saves.

    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 5 optional parameters, no output schema, and no annotations. The description gives a good overview but lacks details on return values, side effects, or failure modes. It could be more complete by explaining what the tool returns or how it interacts with the workflow state, especially given the absence of an 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?

    The input schema already covers 100% of parameters with descriptions. The description adds marginal value by mentioning the default save location and mapping content types to parameters (tests, timing, diff), but does not enrich the semantics of output_path or workflow_id beyond what the schema states. 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 the tool generates a detailed markdown report for a completed feature workflow, listing the specific contents (test results, build status, timing, git changes). This specific verb+resource combination distinguishes it from siblings like generate_test_template (which generates templates) and get_test_results (which retrieves test results).

    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 clear context by stating the tool is for a 'completed feature workflow', implying it should be used after feature completion. However, it does not explicitly mention when not to use it or name alternative tools, so it stops short of a 5.

    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 no annotations, the description carries the full burden of behavioral disclosure. It does add context by stating 'without merging,' which clarifies that changes will not be integrated. However, it does not disclose the destructive nature of aborting (e.g., whether changes are discarded or if the operation is reversible), leaving the agent without full transparency about consequences.

    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 only two sentences: 'Aborts worktree without merging. Use when feature is cancelled.' It is concise, front-loaded with the core action, and every word contributes meaning. No filler or redundancy.

    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 simplicity (2 params, no output schema), the description adequately covers its purpose and usage context. It tells the agent what the tool does and when to use it, while parameter details are fully captured in the schema. It doesn't explain post-abort behavior, but for a cancellation action this is not a critical gap.

    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 having clear descriptions ('Path to worktree' and 'Reason for abort (for logging)'). The tool description itself adds no additional parameter information, 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 clearly states the tool's action: 'Aborts worktree without merging.' This is a specific verb with a resource and a qualifier that distinguishes it from sibling tools like cleanup_worktree. It also provides a clear use case: 'Use when feature is cancelled,' which further clarifies its purpose.

    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 when feature is cancelled,' giving a clear context for when to invoke this tool. It does not explicitly mention when not to use it or name alternative tools, but the provided condition is specific enough to guide selection. This is a clear context without exclusions, meriting a 4.

    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, the description carries the full burden. It discloses key behaviors: saving state, resetting health score, and returning 'health before/after and entries saved.' It also explains the rationale (prevent loss to compaction), adding context beyond the schema. It does not detail every edge case but is transparent enough for a tool of this simplicity.

    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 three sentences with no wasted words. It front-loads the primary action and includes usage guidance and return information 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 simple tool with no output schema and full schema parameter coverage, the description covers the essential aspects: what it does, when to use it, and what it returns. It could benefit from explicit exclusions or alternatives, but the context signals (sibling names) help fill that gap.

    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 already provides 100% coverage of all three optional parameters with descriptions. The tool description adds no additional parameter-specific details 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.

    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 function: 'Save the current workflow state and reset health score.' It also differentiates by mentioning 'before context is lost to compaction,' which distinguishes it from generic save_context. However, it does not explicitly name sibling alternatives, 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 Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides explicit usage guidance: 'Use when health is critical or before long operations.' This tells the agent when to invoke the tool, though it does not discuss when not to use it or mention alternative tools, which would make it more comprehensive.

    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 no annotations, the description carries the transparency burden. It discloses sorting behavior ('by importance and recency') but doesn't state whether the operation is read-only, how empty results are handled, or query semantics beyond the schema. It adds some behavioral detail, but not comprehensive.

    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, front-loaded with the core action, then enumerating key filters. No fluff or repetition; every sentence contributes meaning.

    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 query tool with 7 parameters, no output schema, and no annotations, the description covers the essential behavior: what it queries, what filters are available, and result ordering. It doesn't describe return format, but that's less critical given the tool's nature. It's slightly incomplete on matching semantics, but overall well-rounded.

    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 a summary of filter categories (content, type, tags, workflow, file path) but doesn't explain parameter-specific details beyond what the schema already provides, such as 'any tag' matching or default limit.

    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 ('Query') and identifies a clear resource ('the knowledge graph' for 'relevant memories'). It lists distinct filtering dimensions, distinguishing it from sibling context-management tools like save_context and get_context_health.

    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 clearly indicates when to use the tool: to search memories by content and apply filters (type, tags, workflow, file path). It doesn't explicitly name alternatives, but the tool's read-oriented purpose is evident alongside sibling tools that save/restore context or manage worktrees.

    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 no annotations provided, the description carries the full burden of behavioral disclosure. It transparently lists the core actions (abort worktree, clean up branch, record reason), which conveys destructiveness and logging. However, it does not explicitly state that the branch is deleted by default (though implicit in 'cleans up branch') or mention irreversibility. It's adequate but not exhaustive.

    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, front-loaded with the primary action, followed by usage guidance. Every word earns its place — no redundancy or filler. The format is efficient and easy to scan.

    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 tool with moderate complexity (3 params, 1 required) and no output schema or annotations, the description covers purpose, actions, and usage context. It doesn't explain the default deletion of the branch or the post-rollback state, but these are partly covered by the schema. Overall, it provides enough context for an agent to decide when and 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?

    The input schema has 100% description coverage for all three parameters, so the baseline is 3. The description adds minimal parameter-specific meaning: 'records reason' alludes to the required 'reason' parameter, but doesn't explain 'keep_branch' or 'worktree_path' beyond what the schema already says. Since the schema already documents them, no significant extra value is added.

    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 function: 'Rolls back a failed or unwanted feature' and specifies concrete actions: 'aborts worktree, cleans up branch, records reason.' This distinguishes it from sibling tools like abort_worktree, which likely only aborts the worktree, while rollback_feature handles the full cleanup. The verb 'rolls back' and resource 'feature' are specific and unambiguous.

    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 explicit when-to-use guidance: 'Use this when you need to abandon a feature without merging.' This tells the agent the appropriate context and implies it's not for completing or continuing a feature. It doesn't explicitly name alternatives or exclusions, but the 'use when' directive is clear enough.

    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 no annotations, the description carries the burden of disclosing side effects. It lists three core behaviors (creates worktree, sets up environment, initializes tracking), but the language is vague—'sets up environment' and 'initializes tracking' lack specifics. It doesn't mention prerequisites, reversibility, or potential impact on existing branches, leaving gaps in 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 two sentences, front-loaded with the primary verb and resource, and immediately conveys the key steps. Every word earns its place, with no redundancy or filler.

    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 (4 parameters, no output schema), the description provides a solid high-level overview of the workflow and its recommended usage. It doesn't explain the exact output or post-conditions, but the schema and sibling context fill in many gaps, making it 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 schema has 100% coverage with detailed parameter descriptions, so the baseline is 3. The tool description adds contextual context ('full workflow') but does not elaborate on individual parameters beyond what the schema already provides, so it neither adds nor detracts from parameter clarity.

    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 'Starts a new feature with full workflow' and explicitly lists the steps involved (creates worktree, sets up environment, initializes tracking). It distinguishes itself from the sibling create_worktree by emphasizing the full workflow and positioning itself as the recommended entry point for development work.

    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 guidance on when to use the tool: 'This is the recommended way to begin any development work.' It does not explicitly mention when not to use it or name alternatives, but the context is clear enough for an agent to select it for starting new work.

    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 no annotations, the description carries the full burden of disclosing behavior. It explains the process (Keep a Changelog format, auto-detection, categorization) but does not mention that the tool modifies CHANGELOG.md, potential destructive overwriting, or preconditions like package.json existing. This is useful but incomplete for a mutation tool.

    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 three short, front-loaded sentences. 'Syncs CHANGELOG.md with workflow information' immediately conveys the core purpose, and the following sentences add essential detail without waste. 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 moderate complexity (5 optional params, no output schema, no annotations), the description provides a solid overview of what the tool does and its key behaviors. It could be more complete by mentioning side effects or when to prefer other tools, but it is sufficient for basic understanding and 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?

    The schema has 100% parameter description coverage, so the baseline is 3. The description adds some context (e.g., 'categorizes changes based on feature type' relates to the category parameter) but largely repeats what the schema already documents. No additional parameter-level meaning is provided.

    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 'Syncs CHANGELOG.md with workflow information,' providing a specific verb and resource. This clearly distinguishes it from sibling tools, as no other sibling targets CHANGELOG.md. Additional details like 'Follows Keep a Changelog format' further clarify its scope.

    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: it is for syncing CHANGELOG.md with workflow data and mentions auto-detection of version and categorization. However, it does not explicitly state when to avoid using it or suggest alternatives (e.g., update_documentation), so it misses the highest tier.

    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 no annotations provided, the description carries full burden. It clearly indicates a read-only list operation ('lists'), but it does not disclose behavior such as whether it modifies state, permissions required, or how 'metadata' is defined. It is not contradictory, but it is minimal.

    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, well-structured sentence that conveys the core purpose without any filler or redundancy.

    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 zero-parameter list tool with no output schema, the description is mostly complete. It identifies the resource and scope, though 'metadata' is vague and the absence of an output schema means it doesn't clarify what exactly is returned.

    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 tool has zero parameters, so the description has no parameter semantics to explain. Baseline 4 applies because there are no parameters to document.

    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 ('lists') and resource ('active worktrees') and adds scope ('with their metadata'). It clearly distinguishes this from sibling worktree management tools like create_worktree, cleanup_worktree, and abort_worktree.

    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 is implied: call this when you want to list active worktrees. However, there is no explicit guidance on when to use this versus alternatives, nor any exclusions or prerequisites. It simply states what it does.

    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 no annotations, the description must bear the weight of behavioral disclosure. It explains the tool persists context to memory and captures file changes, but does not mention whether repeated calls overwrite or append, if it requires specific permissions, or what happens after saving. This is acceptable but leaves some side-effect ambiguity.

    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, directly front-loaded with the action, and every clause earns its place. It avoids redundant restating of parameter names and gets straight to the point. No fluff.

    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 no-output-schema, no-annotations tool with five optional parameters, the description covers purpose, typical usage timing, and what is captured. It does not differentiate from sibling checkpoint_context or describe the return value, but it is sufficiently complete for a simple save operation.

    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 schema already provides 100% coverage for all five parameters, so the baseline is 3. The description adds value by mentioning 'file changes' as a captured element, which is not a parameter but indicates automatic behavior, and 'decisions, learnings' align with the decisions and learnings parameters. This extra context meaningfully enriches 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 opens with a specific verb+resource: 'Save the current workflow context to memory.' It then clarifies what is captured (decisions, learnings, file changes) and the purpose (future sessions), clearly distinguishing it from siblings like get_memory and restore_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 provides clear usage context: 'Use this to persist important context before completing or rolling back a feature.' This tells the agent when to invoke it, though it does not explicitly mention alternatives or exclusions. The guidance is sufficient for most workflows.

    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, the description bears full responsibility for behavioral disclosure. It warns that the operation merges and removes the worktree, establishes a testing gate, and cautions against force bypass. However, it doesn't describe failure behavior or whether the merge is a fast-forward or creates a commit.

    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 three sentences with no fluff: purpose, prerequisites, and force warning. It is front-loaded and each sentence adds critical 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 destructive tool with three parameters and no output schema, the description covers the essential usage context: what it does, what must happen first, and the safety valve. Minor gaps like failure handling don't undermine its 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 description coverage is 100%, so all three parameters (force, worktree_path, commit_message) already have descriptions. The description adds a caution about force=true, but this duplicates the schema's warning. No additional parameter context is provided.

    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 a specific action: 'Merges worktree to main and removes it.' This clearly defines the tool's function and differentiates it from siblings like abort_worktree, which cancels instead of merging.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    It explicitly states the prerequisite: 'REQUIRES tests and build to pass first! Run run_e2e_tests and verify_build before calling this.' This tells the agent exactly which sibling tools to run beforehand, and the warning 'Use force=true to bypass (NOT recommended)' provides a clear when-not scenario.

    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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