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aos-standard

MCP Agent Health Reporter

by aos-standard
OverviewSchemaRelated ServersScoreDiscussions
Python

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one performs a health scan on a specific agent, the other is a self-connectivity check. No overlap or ambiguity.

    Naming Consistency5/5

    Both tools follow the consistent pattern 'aos_agent_health_<verb>', using snake_case and clear verb descriptors ('scan' and 'self_test').

    Tool Count3/5

    Two tools is minimal but acceptable for a focused health reporter. However, the server's scope feels limited, bordering on thin.

    Completeness2/5

    Missing obvious operations like listing agents, batch scanning, or retrieving historic results. The surface covers only one core action and a connectivity test, leaving significant gaps.

  • Average 3.5/5 across 2 of 2 tools scored. Lowest: 2.6/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 4 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.

  • This repository includes a glama.json configuration file.

  • 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.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description carries the full burden. It says 'self-connectivity check' but then 'returns sample scan JSON', which is contradictory—it implies a real connectivity test but returns mock data. The tool's true behavior (produces a sample, not a real check) is not clearly disclosed.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

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

    The description is a single, concise line. However, it sacrifices clarity for brevity by not explaining the tool's behavior or parameter.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool has one parameter and an output schema, the description should provide more context (e.g., what the sample JSON looks like, when to set mock to false). It lacks completeness for a tool that is meant for verification.

    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?

    The single parameter 'mock' (boolean, default true) is not described. With 0% schema description coverage, the description must explain it but fails to do so. The agent has no way to know what 'mock' controls.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

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

    The description states 'self-connectivity check' and 'returns sample scan JSON for MCP wiring verification', clearly indicating a health test that produces sample output. However, it does not distinguish from the sibling tool 'aos_agent_health_scan', which likely performs a real scan.

    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 is provided on when to use this tool versus the sibling 'aos_agent_health_scan'. The description does not specify contexts (e.g., testing vs. production) or when to choose one over the other.

    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 burden. It explains behavior: scans agent, returns health score, mock mode for CI (no filesystem reads), and defaults for target_dir. It does not mention side effects, but it is likely a read-only operation. Transparent enough for an agent scan 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?

    Description is very concise: one-sentence purpose followed by bullet-style parameter explanations. Every sentence adds value; no wasted words. Front-loaded with main action.

    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 output schema exists (context: 'has output schema: true'), description is not required to explain return values. It covers purpose, parameters, and mock behavior adequately. Small gap: doesn't specify if the health score is a number or structure, but output schema handles that.

    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 0%, but description adds meaning to all three parameters: tool_id is a four-digit agent id with example, target_dir is root directory with default options, mock is boolean for deterministic CI output. This compensates well for lack of schema documentation.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

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

    Description clearly states it scans a single AOS agent by tool_id under target_dir and returns a health score. The verb 'scan' and resource 'AOS agent' are specific and distinct from the sibling tool 'self_test' which likely tests the agent itself.

    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?

    Description implies usage for scanning a single agent but does not explicitly provide when-to-use or alternatives compared to the sibling tool. No guidance on 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.

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