Lab Registry Server

Server Quality Checklist

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Latest release: v0.3.0
Disambiguation4/5
Most tools have distinct purposes, but check_compliance and check_compliance_plugin overlap in checking compliance at different granularities, which could cause minor confusion. Overall, tools are well-differentiated.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with underscores (e.g., get_entry, list_plugins, suggest_entries). No mixing of conventions or ambiguous verbs.
Tool Count5/5
With 15 tools, the server covers the registry domain comprehensively without being bloated. Each tool serves a clear purpose and earns its place.
Completeness5/5
The tool surface covers all key operations for a registry: listing, searching, getting details, compliance checking, installation, validation, and reloading. No obvious gaps for the stated purpose.
Average 4.2/5 across 15 of 15 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 31 commits in the last 12 weeks
- Last stable release on July 10, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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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.
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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains the return structure (manifest plus list of entries), which provides behavioral insight beyond the input schema. However, with no annotations, it omits details like auth requirements, rate limits, or potential side effects, which are moderate gaps.
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 very concise (two lines for purpose, then bullet points for output). Every sentence adds value, and the structure is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one parameter and an output schema, the description covers the return structure but misses parameter semantics and usage context. It is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fails to explain the 'plugin' parameter at all. It does not specify whether this is a name, ID, or slug, leaving the agent guessing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves 'all registry entries for a plugin plus its manifest.' The verb 'get' and noun 'plugin' are specific, but it does not differentiate from sibling tools like 'get_entry' or 'list_entries'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'get_entry', 'get_entry_by_id', or 'list_plugins'. The description lacks any situational context or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description fails to disclose behavioral traits such as read-only status, authentication requirements, or rate limits. It only enumerates return fields, leaving the agent uninformed about side effects or constraints.
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 reasonably concise, with a clear purpose sentence followed by a bulleted list of return fields. It front-loads the key verb and resource. Minor improvement could be made by grouping related output fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description explains return values adequately. However, it lacks usage context (when to call) and does not mention that results reflect the entire registry, which is a significant omission.
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 has zero parameters, so no additional meaning is required. The description implicitly conveys that no filters are needed, which is adequate for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'dashboard overview of the entire registry'. This distinguishes it from sibling tools like get_entry and list_entries, which focus on specific entries or lists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like list_entries or get_plugin. It only lists return fields without specifying context (e.g., 'Use for high-level registry statistics').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses tags use OR match, but lacks mention of pagination, limits, or default behavior when no filters applied. Without annotations, more behavioral details would be beneficial.
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?
Short and front-loaded: the main action in the first sentence, followed by a clean list of filter options. Each sentence serves a purpose with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (not shown), so return values are not needed. The description covers filters and tag logic, but pagination info is missing. Overall, fairly complete for a listing tool with 3 optional params.
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 0%, yet the description adds meaning by listing possible values for type (skill, agent, command, hook), examples for plugin (android, delivery, research-suite), and clarifying tag matching logic. This compensates well for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List all registry entries' with specific filter options (type, plugin, tags), distinguishing it from siblings like list_plugins (only plugins) and search_entries (likely more advanced).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use list_entries versus alternatives such as search_entries, get_entry, or list_plugins. The description only explains how to filter but not when to choose this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It explains the core workflow (discover local files, read versions, compare) and the return structure (outdated, unknown, up_to_date_count). However, it does not mention side effects (likely none), authentication needs, or error handling. The description is adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, then provides usage guidance, workflow, parameter details, and return structure. It is well-structured and each sentence adds value. Slightly verbose but not wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity, the output schema is present (context signals indicate true), and the description explains return values in detail. It covers the tool's behavior adequately. Minor omissions like empty input handling or error conditions are acceptable for a read-only compliance check.
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 has one parameter (entries) with 0% description coverage. The description compensates by detailing the required fields for each entry (name, type, plugin, local_version) and providing examples. This adds significant meaning beyond the schema, which only specifies an array of objects.
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 checks locally installed gen-e2 plugin artifacts against the registry for updates. It uses specific verbs ('Check') and resources ('gen-e2 plugin artefacts'), and the purpose is distinct from sibling tools which are for retrieval or 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 tells when to use this tool ('whenever the user asks to verify, check, or audit'), and provides a workflow including the instruction to not compare versions manually. It does not mention when not to use it or list alternatives, but the guidance is clear and helpful.
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 full burden. It describes the return values (plugin, version, changelog_raw with null case), offering good insight into behavior. No side effects noted, but as a read operation this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise, front-loaded with the main purpose, then usage hint, then return fields. No unnecessary words, well structured.
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 simplicity (one parameter, read operation), the description covers the purpose, usage context, and return structure. With an output schema present, it provides sufficient completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'plugin' is a string; the description does not add meaning beyond the schema property name. Schema coverage is 0%, but the parameter is self-explanatory. Score reflects adequate but not enhanced sematics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Get the full CHANGELOG.md content for a plugin', providing a specific verb and resource. While it doesn't explicitly distinguish from siblings, the mention of being useful after check_compliance hints at differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a concrete usage scenario: 'Useful after check_compliance signals an outdated entry.' It implies when to use but lacks explicit exclusions or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries full burden. It describes the return shape (same as check_compliance with outdated, unknown, up_to_date_count), implying read-only behavior, but does not explicitly state safety, authorization needs, rate limits, or side effects. The description is adequate but lacks explicit behavioral guarantees.
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 with three concise paragraphs: a clear first line, a usage guideline paragraph with workflow, and a return shape paragraph. No fluff, every sentence adds value, and it is well-structured for quick reading.
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 presence of an output schema (which explains return values), the description covers purpose, usage, differentiation, and return shape. It lacks explicit mention of error cases or prerequisites (e.g., plugin must exist in registry), but overall it is sufficiently complete for effective tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, so the description must compensate. It mentions 'local version' and 'plugin.json with one version field' in the workflow, linking 'plugin' to a plugin name and 'local_version' to a version string for comparison. However, it does not detail format constraints (e.g., semver) or validation rules, providing only partial semantic enrichment.
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 'Check all artefacts of a gen-e2 plugin against a single local version', specifying the verb 'check', the resource 'artefacts of a plugin', and distinguishes from sibling 'check_compliance' by noting it performs batch verification instead of manual per-artefact calls.
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 when you have a plugin.json with one version field and want to verify the whole plugin in one call, instead of listing artefacts manually and calling check_compliance with each one.' Provides a typical workflow with steps, giving clear context for when and how to use this tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions return shape and gives an example, but doesn't explicitly state read-only nature, error cases, or authorization. Adequate but could be more 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?
Four sentences, each serving a purpose: description, usage guidance, return shape, example. No redundant text. Efficient 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 simplicity (one parameter, output schema exists), description covers purpose, usage, return shape, and example. Doesn't mention error handling or performance, but sufficient for the tool's scope.
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?
The only parameter 'id' has no description in the input schema (0% coverage). The description compensates fully by explaining the format ('plugin/type/name') and providing an example, making it easy for an agent to construct valid input.
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 retrieves a registry entry by its full ID, distinguishing it from get_entry by noting it's a shortcut when you already have the ID from list_entries. The verb 'get' and resource 'entry' 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?
Explicitly says 'Shortcut for get_entry when you already have the entry ID from list_entries,' providing clear context on when to use this tool over alternatives. Does not state when not to use, but implication is 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?
No annotations provided, so description carries full burden. It describes return fields (content_full, install_targets, plugin_tracking) and their usage details. Does not cover auth or side effects, but for a read-like tool the output description is 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?
The description is well-structured with bullet points and front-loaded purpose. It is fairly long but each sentence adds value. Could be slightly tighter but overall efficient for the information conveyed.
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 presence of output schema, the description provides sufficient context: what the tool returns and how to interpret it. It lacks error handling or prerequisites, but is largely complete for its simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% for the single parameter 'plugin'. The description does not elaborate on its format or constraints beyond the tool context. It relies on the parameter name and tool purpose to convey 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 the tool's purpose: 'Get full documentation AND install-ready files for an entire plugin in one call.' It distinguishes from siblings like get_entry by noting this is for full plugins vs individual entries.
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 clear when-to-use scenarios: 'install a plugin... get the documentation and install files... know where to place artefacts.' Also explicitly suggests preferring this over multiple get_entry calls, offering an alternative.
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?
Without annotations, the description adequately conveys that this tool performs read-only validation with no side effects. It lists return values but does not explicitly state non-destructive behavior, though it is implied.
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 succinct, using bullet points for parameters and return values. No redundant information; every sentence serves a 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?
The description covers the tool's purpose, parameters, and return format comprehensively. Given no output schema, including the return structure is beneficial. Minor omissions like error handling do not detract significantly.
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 description adds significant meaning beyond the schema by explaining the content parameter as full file content with YAML frontmatter and listing allowed values for type (skill, agent, command, hook). With 0% schema coverage, this compensation is effective.
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 validates a skill/agent/command markdown file against a marketplace schema, specifying the types of files and checks performed. It distinguishes from siblings by focusing on validation, unlike tools like get_entry or check_compliance.
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 for pre-submission validation, but does not explicitly contrast with siblings like check_compliance. No alternative tool comparisons are provided, so usage context is implied only.
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 discloses the return structure (sorted, alphabetical, fields including entry_counts). It lacks mention of performance or state implications, but for a read-only list, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-loading the purpose and listing output fields. Every sentence adds value with no 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?
Even with an output schema, the description fully covers returned data, sorting, and entry_counts structure. No gaps given zero parameters and simple semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters (schema coverage 100%), baseline 4. The description adds value by detailing output fields and nested structure, compensating for lack of parameters.
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 lists all plugins with version, description, and entry counts per type. It specifies sorted order and explicit fields, distinguishing it from siblings like list_entries (entries vs plugins) and get_plugin (single vs all).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied for listing all plugins, but no explicit guidance on when to use vs alternatives (e.g., search_entries, get_plugin) or when not to use it.
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 details the return structure (entry, metadata, content_raw, content_full, install_targets), disclosing exactly what the tool outputs. It implies a non-destructive read operation without hidden side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficient: two sentences for purpose/usage and a bullet list for outputs. No redundant information, every part adds value.
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?
While the output fields are well described, the description lacks parameter explanations. Given the tool has a moderate complexity (3 required params) and no schema descriptions, the description is incomplete without parameter semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the three required parameters ('plugin', 'type', 'name'). Despite having output details, the parameter semantics are absent, requiring the agent to infer their meaning from context.
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 retrieves a specific registry entry with full content, using the verb 'get' on the resource 'registry entry'. It distinguishes from the sibling tool 'get_plugin_install_package' by noting the latter retrieves all artefacts at once.
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 ('to read a single artefact's documentation or to get its install files') and when not to, providing the alternative tool name 'get_plugin_install_package' for bulk retrieval.
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 details search behavior: fields searched, ranking logic, and type restriction. However, it does not explicitly state that it is read-only or mention any potential side effects, which would be expected for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with five sentences, front-loading the core action and efficiently providing key details without 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?
Covers input behavior, ranking, and type restriction adequately. With an output schema present, the description need not explain return values. However, it omits potential details like pagination or ordering beyond ranking, which are minor 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 coverage is 0%, so the description must explain parameters. It describes 'query' as an exact keyword or partial name and mentions optional type restriction, but lacks specifics on 'type' values or query format details (e.g., case sensitivity). Adds meaning but could be more comprehensive.
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 searches registry entries by exact or partial name, matching against name, description, and plugin name, with ranking and optional type restriction. It distinguishes itself from the 'suggest_entries' sibling, making 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 states when to use (specific keyword or partial name) and when not to (natural language tasks, suggesting 'suggest_entries' instead), providing clear guidance with examples.
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 full burden. It discloses key behavioral traits: clears in-memory cache, re-fetches all entries, and returns a diff of added/removed/modified IDs. While it doesn't discuss performance or authorization, the side effect and return format are well explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a one-sentence purpose, a usage guideline sentence, and a bullet list for return details. 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?
Given the zero-parameter complexity and the presence of an output schema (evidenced by context signal), the description is complete. It covers purpose, usage, side effects, and return format in detail, leaving no significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, so the description does not need to add parameter semantics. Baseline 4 is appropriate since the schema coverage is 100% and there are no properties to describe.
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 a clear action statement: 'Force reload the registry from its source (GitHub or local path).' It specifies the resource and the verb, clearly distinguishing this tool from listing and search siblings, which do not reload.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says when to use it: 'Use after a marketplace update (git pull / new commit) to get fresh data without restarting the server.' It does not mention when not to use or alternatives, but the context is clear enough for an AI agent to infer appropriate usage.
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?
Explains the scoring mechanism (splits task into terms, scores by term matches) and ranking. Lacks explicit mention of non-destructive nature or idempotency, but overall reasonable given no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise, front-loaded, every sentence adds value. Structured with main purpose, then usage, then parameters. No unnecessary text.
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 an output schema exists, the description doesn't need to explain return values. It covers behavior, parameters, and use cases adequately for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully explains each parameter: 'task' as natural language description, 'type' as optional filter, 'limit' with default. Adds meaning 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 suggests registry entries relevant to a natural language task description. It distinguishes itself from the sibling 'search_entries' by specifying it's for natural language queries vs. exact keyword matching.
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 for natural language queries like 'I need to review architecture' and for exact keyword matching use 'search_entries' instead.
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 fully bears the burden. It explains the scoring mechanism (word matching with 3x weight on plugin names), sorting by relevance, and gives examples. This provides comprehensive insight into the tool's behavior without contradiction.
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: purpose, usage guidelines, behavioral details, examples, and parameter definitions. Every sentence adds value without repetition, and it remains concise while covering all essential aspects.
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 simplicity of the tool (2 parameters, one required) and the presence of an output schema (not shown but noted), the description provides complete contextual information. It explains when to use it, how it works, and what parameters are needed, leaving no critical gaps for an AI agent.
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 0% schema description coverage, the description adds necessary meaning: 'task: natural language description of the project or need' and 'limit: max results to return (default 5)'. This is helpful but could be slightly more detailed about the task format or limit constraints.
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 the tool's function: 'Suggest gen-e2 plugins relevant to a natural language task or project description.' Uses a specific verb (suggest) and resource (plugins), and distinguishes from the related sibling 'suggest_entries' by emphasizing plugin-level discovery before drilling into individual artefacts.
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 tells when to use the tool: 'Use this for plugin-level discovery when the user describes their project or use case and wants to know which plugins are most relevant — before drilling into individual artefacts with suggest_entries.' Also provides examples of typical inputs and outputs, giving clear context for appropriate invocation.
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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