Mikes Moose MCP

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Each tool has a distinct role: search/lookup/class_tree for reference, example/practice for guidance, parse_log/tail_log for runtime analysis, and parse_mission for mission data. The only possible overlap is parse_log vs tail_log, but descriptions clearly separate full-session parsing from incremental tailing.
Naming Consistency3/5
All tools share the 'moose_' prefix and snake_case, but the suffix pattern mixes verbs (ingest, lookup, search, validate), nouns (example, practice, instances), and verb_noun compounds (parse_log, tail_log, parse_mission). This is readable but not a single consistent convention.
Tool Count5/5
With 11 tools, the server covers a comprehensive MOOSE workflow—indexing, querying, validating, log/mission parsing, and instance management—without excess. Each tool addresses a clear need, fitting well within the 3-15 sweet spot.
Completeness4/5
The tool set covers the major pillars of MOOSE development: framework reference, practice rules, runtime truth, mission truth, and validation. Minor gaps like removing indexed entries or listing all classes are workable via existing tools (e.g., re-ingest or search).
Average 4.3/5 across 11 of 11 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 18 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How 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?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: every CLASS:METHOD call is looked up, unknown methods/classes are flagged, and deprecated-class or pcall-on-lookup anti-patterns are surfaced. This goes beyond a simple 'validates' statement and gives a clear picture of the validation logic, though it could further clarify the output format or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, with two sentences total. The second sentence is highly informative. The opening 'Correlation core' is somewhat cryptic and does not immediately clarify the tool's purpose, which slightly reduces structure quality, but overall it is concise and free of redundant fluff.
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 there is no output schema or annotations, the description explains what the tool does and what it flags, but does not describe the return value format or error behavior. For a validation tool, it would be more complete to state what the output looks like (e.g., a list of issues), making this a gap. The low parameter complexity reduces the burden, so the description is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with one parameter ('code') described as 'The Lua snippet to validate.' The tool description adds some context (e.g., 'generated' snippet, validation against Pillar 1 index), but does not add significant meaning beyond the schema itself, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 verb ('validates') and resource ('generated Lua snippet against the Pillar 1 framework index'), with explicit details about what it checks (CLASS:METHOD lookups, unknown methods/classes, anti-patterns). This distinguishes it from sibling tools like moose_lookup and moose_search, which likely focus on retrieval rather than validation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: use this tool when you need to validate a Lua snippet against the framework index. However, it does not explicitly state when to use it over alternatives (e.g., moose_lookup for simple lookup, moose_example for examples) or provide exclusions, so guidance is only implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the output's scope ('Method names only — no bodies, no docs') and performance expectations ('cheapest query'). It does not mention error handling or side effects, but its read-only nature is implied by 'Returns' and 'query'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary function and followed by a clear use case. Every phrase earns its place; no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter query with no output schema, the description adequately explains the return structure (inheritance chain + method names) and intended use. It could be improved by noting error behavior or formatting, but that is not critical for this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the 'class' parameter with examples, and the description adds no additional parameter-specific meaning. With 100% schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: 'Returns the inheritance chain of a class... plus the list of method names on each class.' It also distinguishes itself from sibling tools by calling itself 'the cheapest query' and focusing specifically on method names.
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 provides a clear use case: 'ideal for checking "what methods does this class have?" quickly.' This gives context but does not explicitly exclude alternatives or name sibling tools, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full transparency burden. It does disclose the primary side effect (remove deletes) and the integration behavior (labels become usable as paths by moose_parse_log and moose_ingest). However, it omits details about persistence, error handling, or whether actions are reversible beyond 'delete.'
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long and front-loaded: it states the tool's purpose, enumerates the actions, and explains the downstream benefit. Every word contributes meaning, with no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple registry tool with five parameters and no output schema, the description is complete enough. It covers the purpose, usage, and integration with sibling tools. The lack of output format details is acceptable because the list/delete operations have self-evident results, though a brief mention of what 'list' returns would have pushed it to a 5.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters, giving the baseline of 3. The description adds value by grouping parameters per action (list, add, remove) and clarifying that 'server vs client' is an instance attribute. It also specifies which parameters are required for which actions, though the schema already notes 'required for add/remove' in individual fields.
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 identifies the tool as a 'Cross-cutting instance registry' with specific actions (list, add, remove) and explains its role in managing DCS installs. It distinguishes itself from sibling tools by focusing on instance registration rather than log parsing or mission validation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states how to use the tool: 'Use action=list to see known instances, action=add to register one, action=remove to delete.' It also explains the benefit of registering an instance (other tools can use the label as a path), but stops short of explicitly describing when not to use it or naming 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?
No annotations are provided, so the description carries the full burden. It transparently discloses copy-on-read behavior, non-execution of the Lua table, and graceful degradation when the file is locked by DCS or the ME. This covers key safety and runtime behaviors, though it does not detail return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the primary purpose, followed by safety behavior and edge-case handling. Every sentence adds value with no unnecessary words, making it concise and well-structured.
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 one parameter, no annotations, and no output schema, the description is quite complete. It specifies the data exposed (group names, unit types, countries, waypoints, trigger names), safety mechanisms, and graceful degradation. It does not explicitly state the return format, but the low complexity and listed data types make the behavior largely inferable.
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 a clear parameter description ('Path to a .miz mission file'), so baseline is 3. The description reinforces the .miz extension and file type but adds no additional syntax or format details beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it parses a .miz mission file to expose real group names, unit types, countries, waypoints, and trigger names. The verb 'Parses' and resource '.miz mission file' are specific, and it distinguishes from sibling tool moose_parse_log by targeting mission files rather than logs.
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 provides a clear use case: 'Kills FindByName misses with the actual entity names,' indicating when to use this tool for resolving entity names. However, it does not explicitly mention when not to use it or name alternatives, so it meets clear context but lacks explicit exclusions.
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?
No annotations are provided, so the description carries the transparency burden. It discloses the stateful behavior (advancing from_line), the return of newFromLine, and the reset-to-0 handling of truncation/rotation. This goes beyond the schema and provides useful context about how the tool behaves over repeated calls.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: 'Tail mode for dcs.log' immediately conveys purpose. Each of the three sentences contributes distinct value: purpose, usage pattern, and robustness. No fluff or unnecessary repetition.
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?
Although there is no output schema, the description mentions 'newFromLine' and 'only new events,' which gives a sense of the return value and behavior. For a simple two-parameter tool with full schema coverage, this is nearly complete, though it could explicitly state the full return structure or error conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage of both parameters, including the meaning of from_line and the instruction to use newFromLine from a previous call. The description reinforces this but does not add substantially new parameter details, so the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the tool as 'Tail mode for dcs.log' and explains it parses only lines after a given line index for near-live following. This clearly distinguishes it from the full-parse sibling moose_parse_log by focusing on incremental tailing.
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 provides explicit usage instructions: call repeatedly and advance from_line from the returned newFromLine to get only new events. It also explains truncation/rotation handling. However, it does not explicitly name alternatives or state when not to use it, but the tail semantics make the use case clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It transparently discloses the key behavior: if no vetted example matches, it returns [NEEDS AUTHOR] and declines authoritative answers, and it never falls back to unvetted community code unless asked explicitly. This covers the main behavioral traits effectively, though it omits any mention of permissions or side effects, which are less critical for a read-only lookup.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the primary purpose, and each sentence adds value: the main action, examples for context, and edge-case behavior. It is concise without being under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description fully covers the return values (matching example or [NEEDS AUTHOR]) and the special behavior. It also provides context about being Pillar 2 and the types of missions, making it sufficient for an agent to understand when and how to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage for the single 'pattern' parameter with examples. The description adds contextual examples (STATIONKEEP, FLEET) but does not materially change the meaning or syntax of the parameter. Therefore, it does not go beyond the schema's 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 returns a matching vetted author example for a pattern, which is a specific verb+resource action. It also distinguishes itself from siblings by emphasizing 'vetted author examples' and its refusal to fall back to unvetted community code, making its role unique among the listed sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for retrieving authoritative, vetted examples and notes that it will not use unvetted code unless explicitly requested. It provides context on when to rely on it, but does not explicitly name alternative tools or situations where those alternatives should be used instead, resulting in a minor gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description discloses important behaviors: re-ingesting is a no-op if the hash is unchanged, and every record is stamped with provenance (file/hash/commit). It does not mention side effects like overwriting existing records or permissions, but the disclosed idempotency and provenance are valuable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description uses four sentences to cover purpose, path examples, source options, idempotency, and provenance. It is front-loaded with the primary purpose and avoids fluff, though slightly longer than strictly necessary.
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 and no annotations, the description covers the essential context: what it does, how to invoke it, default behavior, and idempotency. It could mention how ingested files are used by sibling tools (e.g., lookup/search), but that is reasonably implied in the framework 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?
Schema coverage is 100%, but the description adds meaning beyond the schema by explaining the 'path' example (Saved Games path or UNC), the 'source' enum defaults, and the behavior when 'path' is omitted (bundled GitHub reference). The 'label' parameter is not mentioned in the description, but the schema covers it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Index a Moose.lua file into the framework reference.' It clearly distinguishes this ingest tool from sibling lookup/search tools by focusing on adding data rather than querying 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?
It gives clear context on when to provide a path and when to omit it, and explains the source parameter options and defaults. It does not explicitly name alternatives or exclusions (e.g., 'use moose_lookup for queries'), but the use case is well implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses key behaviors: handles truncation naturally, never blends runs, returns capped token-budget results, and focuses on structured GM events plus error/warning collection. It does not explicitly state whether parsing is read-only, but 'parse' implies non-destructive.
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 and front-loaded with the core purpose in the first sentence. The subsequent sentences add useful detail without redundancy. The phrase 'Pillar 4' is jargon but not excessive; overall it is tightly written.
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 what the tool returns: structured GM events, error/warning lines, and tracebacks. It also covers session handling, truncation, and token-budget limits. It does not specify the exact return format, but the description is sufficient for an agent to understand the tool's scope.
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%, providing descriptions for all four parameters. The description adds meaning by explaining token-budget capping (max_events/max_errors) and session-only behavior via 'this_session_only' through the 'never blends runs' phrase, going beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool parses dcs.log for runtime truth, extracts structured [GM] events, and collects error/warning lines. It uses a specific verb ('parse') with a specific resource (dcs.log) and distinguishes itself from siblings like moose_tail_log (tailing) and moose_parse_mission (parsing a different file).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: to get runtime truth from a log, find session start, and parse errors. It highlights 'never blends runs' and token-budget behavior, but does not explicitly name alternatives or state when not to use it, falling just short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 behavioral traits such as the authoritative hierarchy ('always outrank community code') and the output nature ('small, precise rule records'). While it does not explicitly state read-only behavior, the verb 'Returns' strongly implies it, and the added context goes beyond a basic description.
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 includes actionable guidance. It is slightly repetitive (the word 'Returns' appears twice), but no sentence is wasted; each adds value—purpose, authority, phase meaning, workflow, and output format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool lacks an output schema, but the description partially compensates by stating the return format ('rule records'). It covers phase semantics and the authoritative ranking. It does not specify detailed fields of the rule records or edge-case behavior, but given the tool's moderate complexity, the description is reasonably 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?
With 100% schema description coverage, the baseline is 3. The description adds practical meaning beyond the schema by explaining the Plan/Act workflow, linking phase values to specific times in the workflow (planning vs coding). This enriches the schema's simple enum 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's function: it returns AUTHOR-curated rules for MOOSE usage, with a specific verb (returns) and resource (rules). It distinguishes itself from sibling tools by emphasizing that author rules are authoritative and outrank community code, and by referencing 'Pillar 2'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear workflow guidance, explaining when to use phase=plan vs phase=act ('fire phase=plan during planning, phase=act while writing code'). However, it does not explicitly name alternative tools or state when not to use this tool, relying on the authority claim to imply preference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the return format (name + one-line summary, plus signature/parent where available) and result caps (default 15, max 30). While it doesn't explicitly state read-only, the 'Fuzzy-match' and 'Returns' language strongly implies a non-mutating search operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each earning its place: purpose, output format, limits, and usage guidance. No redundant or filler content, and the key information is 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?
For a simple search tool with two parameters and no output schema, the description fully covers the what, how, and when. It explains the output shape and limits, and with sibling tools like moose_lookup, the usage context is complete. No significant gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no new parameter-specific semantics beyond what the schema provides—the 'limit' default and max are already in the schema. The 'half-remembered' framing is more about purpose than parameter 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 explicitly states a specific verb ('Fuzzy-match') and resource ('indexed Moose.lua'), and it distinguishes from sibling tools by framing the use case ('half-remembered class or method names'). This is a clear, non-tautological 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?
Provides explicit guidance: 'Use this before lookup when you only half-remember a name.' This names the alternative (moose_lookup) and specifies the condition for using this tool over it, making the usage context unambiguous.
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 behavioral disclosure burden. It specifies what is returned (documentation block, signature, return docs, inheritance chain), how method inheritance is handled (inheritedFrom flag), and includes a token-budget warning ('never a dump'). This goes beyond minimal 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?
The description is four sentences, each earning its place: purpose, parameter usage, inheritance behavior, and token budget. It's front-loaded with the primary purpose and contains no filler.
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 no output schema and no annotations, the description provides a complete picture of what the agent can expect: exact content of the returned record, parameter behavior, inheritance handling, and output size constraints. This is sufficient for an agent to select and invoke 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?
The input schema already provides 100% coverage for both parameters, so the baseline is 3. The description adds extra meaning by explaining that when a method is inherited, it is returned flagged as inheritedFrom. This semantic is not present in the schema and helps the agent understand the lookup behavior.
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 returns one precise record from the indexed Moose.lua, listing the exact contents (LDoc block, signature, return docs, inheritance chain). This distinguishes it from sibling tools like moose_search (which would search broadly) and moose_class_tree (which would show a tree). The verb 'Returns' and resource 'indexed Moose.lua' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: class is required, method is optional, and it explains behavior when method is omitted. It also notes that inherited methods are flagged. However, it does not explicitly name alternative tools or state when not to use this tool, so it just misses the explicit 'when-not' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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