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Sudhan30

freshprobe

by Sudhan30
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Server Quality Checklist

75%
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  • Latest release: v0.2.0

  • Disambiguation4/5

    The three tools have distinct purposes—batch processing, single endpoint diagnostics, and policy compliance checking—but check and policy both probe endpoints which could cause momentary hesitation. The differing return types (metrics vs pass/fail) clarify their boundaries.

    Naming Consistency5/5

    All tools follow the identical snake_case pattern with a consistent 'freshprobe_' prefix followed by a descriptive term (batch, check, policy). No mixing of conventions or verb styles.

    Tool Count4/5

    Three tools is on the lean side but appropriate for this focused scope, covering the essential execution modes: single probe, concurrent batch, and policy-evaluated check. Each tool earns its place without redundancy.

    Completeness3/5

    The surface covers execution well but has notable gaps for a freshness monitoring domain: no policy CRUD operations (despite referencing named policies), no historical result retrieval, and no endpoint configuration management. Agents can probe but cannot manage the monitoring lifecycle.

  • Average 3.5/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • 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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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 present, so the description must disclose all behavioral traits. It mentions concurrency and return type, but fails to mention error handling, timeouts, side effects, or performance implications of concurrent probing.

    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 short sentences front-load the purpose and output. Every word adds value; no filler or repetition.

    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?

    For a tool with 3 required params and no output schema, the description captures core purpose and output. However, it omits important context like concurrency limits, error behavior, and what 'verdicts' contain, leaving the agent underinformed.

    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 descriptions for all parameters, so baseline 3 is appropriate. The description adds no extra parameter meaning 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 uses a specific verb ('Probe') and resource ('multiple endpoints'), clearly states the action is concurrent and for 'data freshness', and distinguishes from siblings via the 'batch' name implying multiple endpoints.

    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 siblings like freshprobe_check (likely single-probe) or freshprobe_policy. The agent gets no information about appropriate contexts 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.

  • Behavior2/5

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

    No annotations provided, so the description carries the full burden. It describes the return but not side effects, modification risks, auth requirements, rate limits, or other behavioral traits beyond the probe action.

    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 sentences, front-loaded with purpose, no redundancy or fluff. Every word 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?

    Given 5 parameters, no output schema, and no annotations, the description covers the basic operation and return fields but lacks details on parameter interplay, edge cases, and usage constraints.

    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 descriptions for all 5 parameters. The description adds minimal extra meaning beyond the schema (e.g., mentions deterministic JSON return), meeting the baseline for high coverage.

    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 action ('probe'), the resource ('a single endpoint'), and the output ('deterministic JSON verdict'). It distinguishes from siblings like freshprobe_batch (batch) and freshprobe_policy (policy).

    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 use for single endpoint probing but does not explicitly state when to use this tool vs siblings like freshprobe_batch or freshprobe_policy, nor does it provide exclusions or alternatives.

    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, so the description carries full burden. It states the tool returns a verdict with pass/fail but does not disclose potential side effects, error conditions (e.g., missing policy), or permission requirements. Minimal behavioral detail.

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

    Conciseness5/5

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

    Two concise sentences with no superfluous information. Purpose and output clearly stated in a front-loaded manner.

    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 simplicity and 100% schema coverage, the description adequately covers what the tool does. However, no output schema exists, and the description could elaborate on the verdict format. Still sufficient for a straightforward check 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?

    Schema coverage is 100% with descriptions for both parameters. The description adds no extra meaning beyond what the schema provides, so 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 verb 'check', the resource 'endpoint' against a 'freshness policy', and the outcome 'verdict with pass/fail evaluation'. It distinguishes from siblings by specifically mentioning policy-based evaluation.

    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 use when a named freshness policy exists, but does not provide explicit guidance on when to use this tool over siblings like freshprobe_check or freshprobe_batch. No when-not-to-use or alternatives mentioned.

    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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