Cortex

by igrechuhin

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.2.0
Disambiguation5/5
Each tool addresses a unique aspect of the development workflow: autofix handles fixes, compress and memory_wal manage memory, pipeline_handoff and session handle orchestration, plan and update_memory_bank manage planning and memory mutations, run_* gates run checks, and think provides reasoning. No two tools have overlapping purposes.
Naming Consistency3/5
Names mix verb_noun (run_docs_gate, update_memory_bank, compress_memory_bank) with noun phrases (memory_wal, pipeline_handoff) and bare verbs (autofix, think). The pattern is inconsistent, though all use lowercase and underscores.
Tool Count5/5
10 tools is a well-scoped set for the domain: code quality, memory management, pipeline handoff, planning, sessions, and cognition. No tool seems redundant or missing.
Completeness4/5
The tool set covers the full lifecycle of code quality checks, memory operations, pipeline communication, planning, and session management. Minor gaps exist (e.g., no tool to inspect raw quality gate output without re-running), but core workflows are well-supported.
Average 4.1/5 across 10 of 10 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 58 commits in the last 12 weeks
- Last stable release on April 22, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
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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{
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  "maintainers": [
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  ]
}
```
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint=true, meaning the tool modifies state. The description adds no behavioral context beyond 'lifecycle', failing to explain what gets destroyed, what side effects occur (e.g., during compaction), or any prerequisites like authentication or rate limits.
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 very short (two sentences) and front-loaded with 'USE WHEN', making it easy to scan. However, the extreme brevity sacrifices completeness, and the examples are helpful but insufficient to cover the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 14 parameters, no output schema, and destructive behavior, the description provides almost no context. It omits parameter descriptions, return values, and behavioral details, making it inadequate for an AI agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description only mentions 'goal' and 'summary' in examples, ignoring 12 other parameters like 'blockers', 'decisions_made', and 'create_checkpoint'. The description fails to explain the meaning or usage of these parameters, leaving the agent with no guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Session lifecycle' and provides examples with operations like 'start' and 'compact', giving a clear idea that the tool manages session states. However, it lacks specificity about what exactly 'orientation, registry, compaction' entail and does not differentiate from siblings like 'plan' or 'think', which also manage state.
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 only says 'USE WHEN: Session lifecycle' and shows two example calls. It does not specify when to avoid this tool, nor does it provide alternatives or criteria for choosing between session and sibling tools such as 'autofix' or 'plan'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate destructiveHint=true, and the description implies mutating operations (create, complete, register). However, it does not elaborate on side effects, permissions, or safety considerations beyond the annotation. It adds some context but not significantly beyond what annotations provide.
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 concise, front-loading key information (lifecycle, operations, usage). It includes examples and no superfluous text. While it could be more structured (e.g., bullet points), it is effective and non-verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 21 parameters, no output schema, and destructiveHint=true, the description is severely incomplete. It does not explain parameter roles, return values, or operation-specific behaviors. A tool of this complexity requires much richer documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the 21 parameters. It only references the 'operation' parameter in examples. With zero coverage, the description must compensate but fails entirely, leaving agents without guidance on parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: managing plan lifecycle with operations like create, list, get, complete, register, graph, and archive_completed. It provides examples and usage context. While broad, it effectively conveys the tool's role, and no sibling tool overlaps significantly.
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 includes a 'USE WHEN' section specifying contexts like managing plan files, marking plans complete, registering roadmap entries, or reading the dependency graph. Examples are given. Although explicit exclusions are absent, the guidance is clear and sufficient for an agent to decide when to invoke this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate this is not read-only, not destructive, not idempotent, and not open-world. The description adds context about operation modes and validation/sync rules, but does not disclose return values, error handling, or side effects beyond what's implied by the examples.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a clear purpose sentence, usage guidelines, and examples. It is front-loaded and efficient, earning its keep with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (12 parameters, multiple modes) and lack of output schema, the description is incomplete. It covers high-level purpose and key operations but does not document all parameters or compare with sibling tools like compress_memory_bank or plan, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains a few parameters via examples (operation, section, entry_text, date_str, operation_type, title, summary), but many parameters (position, entry_contains, change_description, skip_classification, section_heading_contains) are undocumented, leaving gaps for the agent.
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 adds/removes roadmap entries and appends memory-bank entries, with specific operation modes (roadmap_add, progress_append, log_append). Examples reinforce the purpose. However, not all operation types are explicitly listed, so it's not a perfect 5.
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?
The description includes explicit 'USE WHEN' and 'DO NOT use' sections, guiding the agent to use this tool for targeted mutations and avoid free-form rewrites. This clearly distinguishes when to use this tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a write operation ('append'), consistent with readOnlyHint=false. However, it does not elaborate on side effects, persistence of the scratchpad, or any behavioral traits beyond the basic purpose, which is acceptable but not thorough.
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: a single sentence for purpose, a usage guideline, and two examples. It is front-loaded with the core action and wastes no words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, no output schema), the description is incomplete. It covers purpose and usage but fails to explain the full parameter set or behavioral nuances, such as how branching and revisions work.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 9 parameters, the description only provides examples for a few (thought, thought_number, total_thoughts, next_thought_needed). Parameters like branch_id, is_revision, revises_thought, branch_from_thought, and needs_more_thoughts are not explained, leaving significant gaps for agent invocation.
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 'Append a thought to internal scratchpad,' providing a specific verb and resource. It distinguishes from sibling tools like autofix or plan by focusing on internal reasoning, and the 'USE WHEN' clause reinforces this differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says 'USE WHEN: Agent needs reasoning before action or multi-step deliberation,' giving clear context for use. It lacks explicit when-not-to-use or alternatives, but the context is sufficient for most cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are minimal (readOnlyHint=false, destructiveHint=false, etc.). The description adds behavioral context: WAL is best-effort, can be disabled by disk errors, and writes still proceed even if WAL fails. This provides useful transparency beyond the annotations, though some behaviors (e.g., restore overwrites) are not fully detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with sections and front-loaded purpose. However, it includes somewhat tangential information about the PreCompact hook and repo bundling, which could be trimmed. Overall, it is clear and fairly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters (0 required, 0% schema description coverage) and no output schema, the description covers operations and use cases but does not explain return values or output format. For a log-inspection tool, information about the structure of returned entries (e.g., anomaly hint format) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%; the description does not define parameters beyond examples. While 'operation', 'label', and 'since' are used in examples, their types, constraints, and default values are not described. The schema provides some structure (anyOf, defaults), but the description adds minimal semantic value. For 0% coverage, this is insufficient.
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 inspects/manages the memory-bank WAL, lists specific operations (read, anomalies, snapshot, restore), and distinguishes itself from git. The verb-resource combination is specific and actionable.
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?
Provides explicit 'USE WHEN' and 'DO NOT' guidance, including context about audit trails and that WAL is not a security auditing tool. Also informs about the absence of a built-in PreCompact hook, steering users to manual snapshot use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate read/write operations. The description adds that data persists in '.cortex/.session/{id}/{pipeline}/,' describes effects of each operation (write, clear, snapshot, rollback), and mentions legacy aliases. This goes beyond the annotations' binary hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with sections (overview, USE WHEN, WORKFLOW, EXAMPLES, RETURNS, Args). While lengthy, each section adds distinct value. Minor redundancy between workflow and examples, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no output schema), the description covers purpose, usage, parameters, return types, and behavioral details (persistence, effects). It is sufficiently complete for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description fully documents all 6 parameters: operation lists possible values, pipeline defaults, phase required/optional constraints, data accepts JSON, paths and snapshot_id for snapshot/rollback, and ctx auto-provided. This compensates fully for the schema gap.
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 it is for 'structured inter-agent communication for pipeline workflows,' uses specific verbs (handoff, init, write, read, clear), and distinguishes from siblings by focusing on pipeline state exchange.
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 'USE WHEN' section explicitly says 'Orchestrators need to exchange structured data between pipeline phases.' It provides a workflow and examples, though it does not explicitly mention when not to use or alternatives.
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?
Describes what it checks and returns. Safe (idempotentHint true, destructiveHint false). Could explicitly state no side effects, but good.
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?
Well-structured with headings, examples, concise. No wasted sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete for a zero-arg tool: covers purpose, usage, returns, and examples. No gaps.
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?
No parameters, schema coverage 100%. Description confirms 'Zero args required', but not much more needed.
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 validates docs/memory-bank sync in Phase B. Specific verb 'validate' and resource 'docs/memory-bank sync'. Distinguishes from siblings like run_quality_gate.
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?
Explicit 'USE WHEN' section and examples. Explains when NOT to use (does not run tests) and provides alternative. Clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only provide readOnlyHint and destructiveHint as false. Description adds critical behavioral context: runs multiple fix types, warns about introducing new failures, and specifies rollback and retry 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?
Well-structured with clear sections: first line summary, USE WHEN, INTEGRITY SAFEGUARDS, EXAMPLES. Every sentence adds value, no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete coverage for a zero-parameter tool: what it does, when to use, side effects, failure handling, and examples. No missing context.
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?
No parameters exist, and description correctly states 'Zero args required'. With 0 params, baseline is 4; description adds clarity beyond 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?
Description explicitly states auto-fix for formatting, linting, type errors, and markdown lint. It distinguishes from sibling tools like run_quality_gate by providing context when to use (Phase A fails) and which agents call it.
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?
Includes a dedicated 'USE WHEN' section specifying condition: Phase A fails and automated fixes needed before re-running checks. Also details integrity safeguards with explicit warnings and limits (max 3 attempts).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses backup creation (.original), structural integrity validation before overwrite, and return of per-file compression ratios. Annotations (readOnlyHint=false, destructiveHint=false) are consistent; description adds behavioral context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with sections (USE WHEN, DO NOT, EXAMPLES, RETURNS). Every sentence adds value; no redundant or vague statements. Front-loads purpose and usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given simple parameter schema and lack of output schema, description covers all relevant aspects: file scoping, safety mechanisms, return structure. Sufficient for correct invocation without additional context.
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 single optional parameter project_root is explained via examples: zero-arg uses workspace root; explicit path sets project_root. Schema has no descriptions (0% coverage), so description compensates well, though more detail on expected format could be 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?
Clearly states it compresses memory bank files (CLAUDE.md, .cortex/memory-bank/*.md) to reduce session token cost. Specifies action, resource, and benefit. Distinguishes from siblings like autofix or memory_wal by targeting memory files.
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?
Includes explicit 'USE WHEN' and 'DO NOT' sections, providing clear context for when to use (after analysis flags candidates, before long sessions) and when not to use (source code, tests, docs outside memory paths). Examples further clarify invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Reveals key behaviors beyond annotations: spawns a detached subprocess, polls with heartbeat notifications, and explains the reflection pass logic. Annotations already provide non-destructive and non-idempotent hints, but description adds operational detail.
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?
Description is well-organized: a concise lead sentence, a 'USE WHEN' section, config details, and examples. No fluff—every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, usage, configuration, and behavior. However, it does not explicitly describe the return value format (e.g., status object structure), which would be helpful given no output schema. Still, it implies results include 'preflight_passed' and 'full result'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has zero parameters, but description adds substantial context by listing supported config keys (coverage_threshold, test_timeout, force_fresh, reflection, force_reflection) and how they are read from a session file. This is far more informative than the empty 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 clearly states the tool runs a quality gate end-to-end and returns full results. It specifically mentions Phase A quality gate and Step 12 final gate, distinguishing it from sibling 'run_docs_gate'.
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?
Explicit 'USE WHEN' section tells exactly when to invoke the tool (commit pipeline Phase A or Step 12 final gate). It also explains prerequisites: config read from a pipeline session file, and shows an example pairing with pipeline_handoff.
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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