Myco

by Battam1111

Overview Schema Related Servers Score Discussions

Rust

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Server Quality Checklist

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Latest release: v0.9.0-alpha.2
Disambiguation5/5
Each tool has a clearly distinct purpose, with no overlap. For example, myco_assimilate and myco_digest both promote notes but differ in scope (bulk vs single), and myco_eat, myco_forage, and myco_intake each serve unique roles in ingestion. The descriptions are precise enough to avoid ambiguity.
Naming Consistency5/5
All tools follow a consistent `myco_<verb>` snake_case pattern. The verbs are unique and descriptive (e.g., germinate, assimilate, excrete, senesce), with no mixing of styles like camelCase or inconsistent prefixes. This makes the tool set predictable and easy to navigate.
Tool Count4/5
With 20 tools, the set is slightly above the typical 3-15 range, but each tool earns its place for a complex knowledge management system. The scope covers lifecycle, introspection, governance, and extension, so the count feels justified rather than bloated.
Completeness5/5
The tool surface is thorough, covering substrate creation, ingestion, promotion, removal, synthesis, propagation, governance, introspection, and extension. No obvious gaps exist for the stated purpose of agent-driven knowledge management. Tools like myco_senesce (session end) and myco_winnow (craft gating) show attention to edge cases.
Average 4.7/5 across 20 of 20 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 2 community issues answered or closed in the last 6 months
- 76 commits in the last 12 weeks
- Last stable release on June 3, 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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
View related servers

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

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations were provided, so the description bears full responsibility. It discloses side effects (writing a cached graph JSON to .myco/state/graph.json), caching behavior, and invalidation based on file mtime. It also explains the return structure. This provides good transparency, though the claim 'Side effects: none' slightly contradicts the cache write, which is a minor inconsistency.
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 structured with clear sections: action, usage, side effects, returns. It is front-loaded with the main purpose and outputs. While somewhat verbose, each sentence adds information. The fungal analogy is engaging but not necessary. Overall, it is appropriately sized for the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains the return fields including orphans, dangling, proposals, and counts. It covers caching and invalidation. However, it does not detail the format of 'proposals' or the structure of the cached JSON. Tool complexity is moderate, and description is largely complete.
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%, so the schema already documents parameters. The description adds value by explaining the scope parameter with valid values and cost implications, and project_dir resolution order. It also mentions an internal parameter 'use_cache' not in the schema, which adds context but could confuse agents expecting it in 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 clearly states the tool walks the substrate's cross-reference graph and reports health metrics, including node count, edge count, orphans, dangling edges, and proposals. It distinguishes from sibling tools by specifying its unique function of graph traversal and health reporting, as evidenced by the concrete outputs listed.
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 scenarios: periodically to detect knowledge islands, before a release to verify docs against code, and when debugging missing references. It also notes the tool is cheap and read-only, implying it can be run often. However, it does not explicitly state when not to use it or compare to alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses no side effects (pure read), adapter priority order, and describes skipped files. However, lacks details on performance implications or error handling for edge cases like permission issues.
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?
Well-structured with clear paragraphs and bullet points for return format. Could be slightly more concise, but overall efficient and front-loaded.
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?
Comprehensive for an adapter-based enumeration tool. Covers purpose, usage, behavioral details, and return structure despite no output schema. No gaps identified.
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 both parameters with examples and descriptions. The description adds little beyond schema, such as single-file preflight behavior, but no new essential meaning.
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 enumerates files that a Myco adapter can ingest, acting as a preflight for myco_eat. It distinguishes itself from siblings like myco_sense (general directory inventory) and myco_eat (bulk ingestion).
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?
Explicitly advises to use before myco_eat to preview ingestible files and warns against using on substrate root recursively, directing to myco_sense instead. Provides clear context.
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 burden. It discloses side effects (file creation, filename collision error), permissions needed (R6 write_surface), and status flow (DRAFT to LANDED). Could be more explicit about safety, but reasonable.
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 front-loaded with the core purpose and structured in clear paragraphs. Some minor redundancy (e.g., the governance metaphor), but overall efficient and well-organized.
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 (scaffolding a multi-round document), the description covers structure, usage, side effects, and return values comprehensively. It also differentiates from siblings effectively. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add much parameter-level detail beyond the schema, but it contextualizes their usage in the broader workflow. Adequate.
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 scaffolds a 3-round craft proposal doc with a specific structure, and distinguishes it from siblings by specifying it is for governance decisions, not feature requests or bug reports (which go to myco_eat).
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 explicitly says 'Use this when: an architectural change needs governance' and 'Do NOT use this for feature requests or bug reports', with a clear alternative (myco_eat).
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?
No annotations are provided, so the description carries the full burden. It discloses side effects (writes to _canon.yaml and changelog), dry-run behavior ('prints the diff'), and version refusal ('down-bumps are refused unless --allow-downgrade is passed at the bump_version.py layer'). It also describes the return object fields, compensating for the lack of an output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with four distinct paragraphs covering purpose, usage, side effects, and return values. It is front-loaded with the main action. While it is somewhat lengthy, every sentence adds value, so it earns a 4 for being appropriately sized and organized.
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 (multiple file writes, version constraints) and the absence of an output schema, the description provides sufficient context: it explains the atomic operation, dry-run preview, return fields, and error conditions (down-bump refusal). It is complete enough for an agent to execute 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 detailed parameter descriptions. The tool description adds no new per-parameter detail beyond what the schema already provides (e.g., contract format, dry_run default). Thus, the description provides marginal added value for parameter semantics, earning the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's core function: 'Ship a contract-version bump' by updating specific fields in _canon.yaml and docs/contract_changelog.md, and advancing a counter. It specifies the verb ('ship'), resource ('contract version'), and distinguishes itself from sibling tools (e.g., myco_assimilate, myco_brief) through unique release-time version management.
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 provides explicit when-to-use guidance: 'AT RELEASE TIME, not during development.' It also specifies when not to use ('Do NOT call this mid-session') and mentions an orchestrating companion (bump_version.py) and an alternative (skip-molt option). This clearly helps an agent choose 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description covers side effects (creates 1 file, requires write surface, collision error), error conditions, and return values. Could mention whether it modifies existing state, but overall thorough.
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?
Well-structured with clear sections (what it does, when to use, side effects, returns). Somewhat lengthy but every sentence adds useful information. Front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers inputs, outputs (return object), side effects, usage context, and error conditions. Lacks output schema but describes return values. Sufficient for a well-understood tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds value: clarifies 'slug' with examples and rules, explains 'sources' auto-selection vs explicit, and describes 'project_dir' resolution order. Exceeds baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Produce a dispersible proposal scaffold by bundling integrated notes into a notes/distilled/d_<slug>.md document'. It distinguishes itself from siblings by naming myco_propagate (cross-substrate sharing) and myco_fruit (contract evolution).
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?
Explicitly states when to use ('when a body of integrated notes have accumulated that belong together') and when not to use ('Do NOT use this expecting auto-synthesis'). Also provides alternative tools for related tasks.
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?
With no annotations, the description fully covers behavioral traits: states 'Side effects: none. Pure read.', details --validate re-imports in isolated namespace and is idempotent. This exceeds the burden without annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections for purpose, usage, side effects, returns. Slightly lengthy but each sentence adds value. No fluff, but could be marginally tighter.
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?
No output schema, yet the description provides detailed return structures for each mode. For a complex tool with 5 modes and zero output schema, this is complete and covers all expected responses.
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 baseline is 3. The description adds context for return formats and mode mutual exclusivity, but does not significantly enhance parameter meaning beyond existing 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 clearly states the tool introspects the plugin surface with operations: list, validate, explain, list-substrates. It explicitly distinguishes from myco_immune's dimension-listing mode, showing good sibling differentiation.
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 when-to-use scenarios: debugging plugin loading, auditing registrations, listing substrates. Also warns what not to confuse it with, making usage guidance thorough.
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?
With no annotations, the description fully discloses behavioral traits: side effects (writes notes to notes/raw/), failure semantics (per-file failures produce stubs, reported in failures list, --strict raises on any failure), and scope (recursive directory scan). It also mentions access control ('R6 write_surface gated') and return payload structure.
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 clear paragraphs for purpose, usage, failure semantics, side effects, and returns. It is front-loaded with the core action. While slightly verbose, every sentence adds value.
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 and lack of output schema, the description provides comprehensive information: what it does, when to use, parameter effects, failure modes, side effects, and the expected return format. It also references the next step (myco_assimilate), closing the loop.
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%, so baseline is 3. The description adds value beyond the schema by explaining practical usage for each parameter: e.g., --filter for regex selection, --max for staged ingest, --strict for full failure mode, and --project_dir for workspace targeting.
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: 'Walk a directory, list every adapter-ingestible file via myco_forage, then call myco_eat on each.' It also distinguishes it from sibling tools by explaining that myco_forage is read-only, myco_eat is single-note, and myco_intake composes both with a write side-effect.
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 states when to use this tool: 'when a fresh substrate needs to absorb an existing directory tree'. It provides guidance on optional parameters like --filter, --max, and --dry-run. It implies alternatives by mentioning single-responsibility composition, though it doesn't explicitly say 'do not use for single file ingest'.
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?
Despite no annotations, the description fully discloses behavior: no side effects, pure read, output to stdout as markdown, nothing written. It also specifies return format (exit_code + markdown) and resolution order for the 'project_dir' parameter.
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 a clear hierarchy: purpose, contents, principle, usage, side effects, return. Every sentence adds value, though slightly verbose. Could be tightened, but 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?
Given 1 optional parameter, no output schema, and rich sibling context, the description is nearly complete. It explains return format, resolution order, and differentiation. Minor gap: no error handling or missing substrate case. Otherwise thorough.
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% and already describes the parameter well. The description adds context about the resolution order and that the 'substrate_pulse' field echoes the source, which complements the schema. Baseline 3 with extra context warrants a 4.
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 produces a human-facing markdown rollup of substrate state, listing specific sections (hunger summary, immune findings, etc.). It distinguishes itself by being the sole exception for human-facing prose, contrasting with sibling tools like 'hunger' (structured) and 'substrate_pulse' (automatic).
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?
Explicitly states when to use (human operator glance, weekly/release-time check-in), when not to use (agent-to-agent reporting prefer 'hunger' or 'substrate_pulse'), and warns against using as input to other verbs. Alternative tools are named directly.
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 side effects: moves file to .myco/state/excreted/, augments frontmatter, and requires .myco/state/ in write_surface. Describes error exit codes (3 for UsageError) and dry_run behavior. No annotations exist, so description fully shoulders 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 well-structured with purpose first, then usage guidelines, side effects, and return value. Every sentence adds necessary information; no filler or repetition. Front-loaded with core action and scope.
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?
Despite no output schema, the description lists return fields (exit_code, note_id, from_path, etc.) and covers error conditions. It explains the audit trail preservation, write_surface requirement, and gitignored tombstones. Sufficient 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover all 4 parameters (100% coverage), so baseline is 3. The tool description adds minor extra context (e.g., dry_run hint to confirm before destructive call) but does not significantly augment schema explanations. No deduction for contradiction, but no extra credit.
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 'Remove a single raw note from notes/raw/' with specific verb and resource. Distinguishes from sibling tools by noting it only applies to raw notes, not integrated/distilled, and explicitly compares to other tools like myco_fruit + myco_winnow for different use cases.
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 when-to-use scenarios (post-myco_eat garbage, myco_hunger shows unwanted raw note) and when-not-to-use (integrated/distilled notes are protected). Suggests alternative tool chain (myco_fruit + myco_winnow) for substantive removal of integrated material.
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?
States 'Side effects: none. Pure read.' and describes return format and typical workflow (fix and re-winnow). No annotations provided, but the description adequately covers behavioral traits for a read-only structure checker.
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 (~150 words) yet packed with essential information. It is well-structured: purpose, usage guidelines, side effects, return format. Every sentence adds value.
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?
Despite no output schema, the description provides detailed return format. Input params are fully documented. The tool's complexity is well addressed with necessary context for correct invocation.
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%, so baseline is 3. The description adds meaningful context for the 'proposal' parameter (path, file requirements) and 'project_dir' (override logic, fallback chain), going beyond 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 clearly states it gates a craft proposal against the craft protocol shape, checking structural requirements like rounds, sections, frontmatter, and boilerplate. It returns pass/fail verdict and specific violations, making the purpose unambiguous.
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?
Explicitly says 'Use this: after fruit scaffolds a craft doc...' and 'Do NOT use winnow as a content quality check... For content review, human judgment still applies.' This clearly specifies when and when not to use, with alternatives.
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?
No annotations provided, but description fully discloses side effects (file creation, atomic O_EXCL create, tag merging), security (SSRF guard), size limits (10MB for URLs), dependencies (myco[adapters]), and return formats for both modes.
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 well-structured with clear paragraphs for purpose, usage, side effects, and returns. Every sentence adds value without redundancy.
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?
Despite no output schema, the description fully explains returns for both content and path/url modes. It covers error conditions, dependencies, and lifecycle context (raw state, assimilation).
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?
Schema coverage is 100% with good descriptions, but the tool description adds mutual exclusivity details, error cases (empty string, more than one), and adapter behavior for path/url.
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 ingests raw material into the substrate: text, file, or URL. It differentiates from siblings by specifying it writes to notes/raw/ and that subsequent myco_assimilate or myco_digest promote it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: use immediately upon capturing insights (R4 of the Hard Contract). Mentions exactly one of content/path/url, but no explicit when-not to use.
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?
No annotations provided, so description carries full burden. It details side effects: no writes by default, with execute=true patching entry-point block. Mentions kill budget and related tool myco_senesce. Fully describes return structure including nested fields. No contradictions.
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?
Description is moderately long but well-structured with sections for purpose, usage, side effects, and return. Every sentence adds value. Could be slightly more concise, but the organization helps readability. 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?
Given the tool's role as a mandatory first action and the complexity of its report, the description fully covers behavior, side effects, return format, and integration with contract rules and other tools. No gaps remain for an agent to misuse it.
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?
Parameter schema coverage is 100% with good descriptions. The description adds context: clarifies execute's write behavior and project_dir's resolution order. This exceeds schema alone, justifying above baseline 3. However, the schema already explains parameters well, so a 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it composes a hunger report with specific components (contract drift, raw backlog, reflex signals, advice, plugin count). It distinguishes from sibling myco_brief by noting this is agent-facing structured data vs human-facing markdown. The purpose is clear, specific, and well-differentiated.
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?
Explicitly instructs to use as the first tool call every session (R1 contract rule) and mid-session for fresh state snapshot. Warns against using as substitute for myco_brief. Mentions idempotency and cheapness. Provides comprehensive when-to-use and when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses side effects: writes to notes/integrated/, boot_brief.md, and may trigger immune --fix. Also outlines return structure including fields like exit_code, findings, reflect, immune, mode. No contradictions with annotations (none provided).
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?
Well-structured with front-loaded purpose, then usage, side effects, and return. Slightly lengthy but every paragraph adds value. Could be more concise, but still effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With only 2 optional parameters and no output schema, the description covers all necessary context: what it does, when to use, side effects, return format, and parameter semantics. No gaps identified.
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?
Input schema has 100% description coverage, so baseline is 3. The description adds context beyond the schema, such as timing expectations for quick mode (1.5s vs 2-5s) and project_dir resolution order. This justifies a 4.
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: 'Put the session into dormancy' and details the two modes (reflect and full immune). It distinguishes itself from siblings by explicitly identifying it as the session-end ritual per the Hard Contract.
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?
Explicitly specifies when to use: at session end before compaction, and when to pass quick=true (abrupt exit with ~1.5s kill budget). It warns against skipping the tool, providing clear context for use vs. alternatives.
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?
Without annotations, description fully discloses side effects (file moves, frontmatter updates, error handling, atomicity, write surface requirements).
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?
Every sentence adds value; front-loaded with main action, well-organized paragraphs without redundancy.
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?
No output schema but description explains return format; parameters fully documented; sibling tools referenced; all behavioral aspects covered.
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%, and description adds meaningful context: explains behavior when note_id is null vs specific stem, and project_dir resolution order.
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 promotes notes from raw to integrated, with explicit bulk vs single-note modes. It distinguishes from sibling myco_digest by noting it's the single-note equivalent.
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 conditions for use (when raw_backlog > 0), warns against premature use, and names alternative tool (myco_digest).
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?
No annotations provided, but description fully discloses side effects: writes 3 files, registers in substrates.yaml, honors R6 write_surface, and that re-calling raises 'substrate already exists'. Also describes return shape and dry_run 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?
Four sentences with no fluff. First sentence nails purpose, followed by usage, side effects, and return structure. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a bootstrap tool with 5 params and no output schema, the description covers all essential aspects: purpose, usage, side effects, return fields, and dry_run option. No gaps identified.
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%, so baseline is 3. Description adds value beyond schema by explaining dry_run behavior ('returns same shape without writing'), preview structure ('first line and byte count'), and R6 write_surface context. However, many schema descriptions are already detailed.
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 starts with 'Bootstrap a new Myco substrate' and lists specific files created (_canon.yaml, MYCO.md, .myco/state/autoseeded.txt), clearly stating its one-time use. It distinguishes from sibling tools like myco_eat by stating when not to use.
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?
Explicitly states when to use ('starting a brand-new substrate that does not yet have _canon.yaml') and when not to (substrate already exists, parent _canon.yaml, or ingest-only) and provides alternative tool name (myco_eat).
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?
No annotations were provided, so the description carries the full burden. It transparently describes side effects (none by default, safe repairs with fix=true respecting write_surface), pure read modes for list and explain, and the return object structure. No contradictions.
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 well-structured: starts with the purpose, then categories, usage guidelines, side effects, and return value. Each sentence adds value without redundancy. It is appropriately sized for the tool's complexity.
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 absence of annotations and output schema, the description provides a comprehensive overview: purpose, categories, when/why to use, behavioral notes on fix and read modes, return structure, and parameter details. It is complete enough for an agent to use the tool correctly.
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%, so baseline is 3. The description adds extra meaning beyond schema: dimensions parameter notes case-sensitivity and hints to use --list; fix details fixable dimensions and write_surface; list and explain explain mutual exclusivity; project_dir mentions response echo field. This additional context raises the score.
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 runs the substrate's 50 lint dimensions and reports findings, categorizing them into mechanical, shipped, metabolic, and semantic types. It distinguishes from sibling tools like myco_sense or myco_brief by emphasizing it checks substrate contract invariants, not application correctness (which is for pytest).
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?
Explicitly states when to use (routinely during development, at release time) and when not to use (not for external code hygiene, use pytest for application correctness). It also specifies the fix=true flag for auto-repair scenarios, providing concrete use cases.
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?
With no annotations, description fully discloses side effects (writes to dst/notes/raw/), the R6 write_surface check applied to destination, dry-run capability, and return structure. Explains that raw notes are never propagated and that receiver re-metabolizes. No contradictions.
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?
Well-structured with clear sections (purpose, when to use, side effects, returns). Some metaphor and philosophical content ('永恒迭代', 'metabolism filter') add flavor but could be trimmed; still earns its place. Front-loaded with key information.
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 5-param, no-output-schema, no-annotation tool: covers prerequisites, behavior differences by parameter, side effects, return values, and dry-run distinction. No gaps for agent invocation.
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?
Schema coverage is 100%, but description adds substantial context: 'dst' explains path resolution and no auto-germinate; 'select' clarifies layers and destination landing; 'commit' explains provenance stamp; 'dry_run' notes default false and effect; 'project_dir' details discovery order. All parameters benefit from narrative explanation.
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?
Describes a specific action: copying integrated/distilled notes from one substrate to another's notes/raw/. Clearly distinguishes from sibling tools like myco_assimilate and myco_germinate by focusing on cross-substrate knowledge push. The metaphor (source-side push) and examples reinforce purpose.
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?
Explicitly states when to use (knowledge sharing between substrates) and when not to (not a git replacement). Specifies prerequisite that dst must have _canon.yaml and that propagation fails without it. Provides clear context for agent decision-making.
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?
No annotations provided, so the description carries full burden. It discloses side effects (creates one Python file), requirements (write_surface, category/severity for dimension, extensions for adapter), error conditions (UsageError if combined kinds, refuse overwrite), and return value structure.
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 well-structured with clear sections: purpose, when to use, side effects, and return. It is concise yet comprehensive, with no unnecessary sentences. Every sentence adds value.
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?
Despite no output schema, the description provides the full return structure. It covers all necessary contextual information for a tool with 9 parameters and multiple modes, including corner cases like auto-detection and force override.
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% with detailed descriptions for each of the 9 parameters. The description adds context beyond the schema, such as auto-detection of substrate-local mode and kernel vs plugin paths. However, the schema already covers parameter details well, so a baseline 3 is raised to 4.
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 'Scaffold the code skeleton for a new extension point' and lists the three kinds (verb, dimension, adapter). It distinguishes kernel vs substrate-local paths, and the name 'ramify' is distinct from sibling tools like myco_assimilate or myco_brief.
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?
Explicitly says when to use: 'to add a new verb / dimension / adapter without hand-writing boilerplate.' Also says when not: 'Do NOT use this to modify existing plugins — ramify is scaffold-only, refuses to overwrite unless --force.' Conditions like mutual exclusivity and write_surface requirements are stated.
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?
With no annotations provided, the description fully discloses behavioral traits: it moves a file from notes/raw/ to notes/integrated/, it is atomic, updates frontmatter, and requires write_surface coverage. It also specifies failure modes and return structure, exceeding basic disclosure.
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, two bullet points for usage, and a list for side effects and returns. It is front-loaded with the core function and uses clear structure. No unnecessary words.
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 no output schema, the description fully explains the return format (exit_code, status, path, etc.) and possible statuses. It covers prerequisites, errors, and sibling tool comparison. The tool has moderate complexity with 3 params, and the description addresses all needed context for correct invocation.
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?
Schema description coverage is 100%, and the description adds meaningful context beyond the schema. For note_id, it advises how to look up stems. For dry_run, it clarifies the no-op behavior. For project_dir, it explains auto-discovery fallback. Each parameter's description 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 explicitly states the tool promotes a single raw note to integrated, using the verb 'promote' and specifying the resource (raw note). It distinguishes itself from the sibling myco_assimilate by contrasting single-note vs. bulk promotion, leaving no ambiguity about its function.
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 provides explicit when-to-use guidance ('one specific note must be integrated right now') and when-not-to-use ('For bulk promotion, use myco_assimilate'). It also details failure conditions (exit_code 3) and side effects, making it clear when this tool is appropriate.
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?
With no annotations provided, the description fully carries the burden of behavioral disclosure. It states side effects are none, it is a pure read, does not touch .myco/state/ or any cache, and details the return format. It also explains that an empty hits array represents a successful call with no matches, which is important for the agent's decision-making.
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 well-structured with clear sections for purpose, usage, side effects, and returns. It is front-loaded with the key action and resource, and every sentence provides essential information without redundancy. Despite moderate length, it is efficient and earns its length.
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 has only two parameters, no output schema, and a large set of sibling tools, the description is remarkably complete. It covers purpose, usage context, behavioral traits, parameter details, return format, edge cases (empty hits), and interaction patterns (composing multiple calls). No gaps remain for the agent to infer.
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?
Although schema coverage is 100%, the description adds significant value beyond the schema: it explains that query is case-insensitive, no regex or glob, and whitespace-only queries return empty hits. For project_dir, it details the resolution order (MCP roots/list, MYCO_PROJECT_DIR, cwd) and that the response echoes which source answered. This greatly enhances parameter understanding.
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 performs a keyword substring search across the substrate's markdown and yaml surface, returning ranked hits with file path, line number, and snippet. It distinguishes itself from siblings by referencing the R3 SENSE-BEFORE-ASSERT mechanism, making its purpose unique and clear.
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 explicitly guides the agent to use this tool before making claims about substrate content, and recommends composing multiple calls with synonyms for broader semantic search instead of expanding the query. It clarifies that the tool is a literal substring scan with no embedding, LLM, or network, providing clear when-to-use and alternatives.
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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