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cliwant

mcp-sam-gov

by cliwant

feedback

Read-only

Report a bug, request a feature, or flag a wrong result. Returns a pre-filled GitHub issue link for you to review and submit.

Instructions

Report a problem, request a feature, or flag a wrong-looking result for THIS server — returns a PREFILLED GitHub issue link (public repo cliwant/mcp-sam-gov) for the USER to open and submit. KEYLESS. The server does NOT post anything: it only builds the link; the human submits it (nothing is sent automatically, no network call). Use when the user reports a bug, says a tool's output looks wrong, or wants a capability this server doesn't have. Input (all optional): kind (bug|feature|wrong_output, default bug), tool (the tool it's about), summary (a short, NON-SENSITIVE title line). Returns { reportUrl, repo, willPost:false, instructions, privacy }. PRIVACY: never put secrets, personal data, or sensitive query values in summary — the issue is PUBLIC and the link prefills only your summary + tool + server version.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoWhat kind of report: bug (default), feature (a capability this server lacks), or wrong_output (a tool returned a wrong/suspicious result).
toolNoThe tool name this is about, if any (e.g. 'sam_search_opportunities').
summaryNoA short one-line summary for the issue title/body. PUBLIC — never include API keys, personal data, or sensitive query values.
Behavior5/5

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

Annotations include readOnlyHint=true, consistent with description stating 'The server does NOT post anything: it only builds the link; the human submits it.' Description adds critical behavioral details beyond annotations, including privacy warnings and no network call.

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

Conciseness4/5

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

Description is front-loaded with purpose and mechanism, then lists inputs and output. Slightly lengthy but all sentences earn their place. Could be trimmed slightly but remains effective.

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

Completeness5/5

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

For a simple 3-param tool with no output schema, the description is exhaustive. It explains return fields, behavior (no automatic posting), privacy, and instructions. No 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?

Schema coverage is 100%, so baseline is 3. Description adds value by clarifying defaults (kind default bug), providing examples, and emphasizing privacy concerns for summary. This extra guidance improves usability.

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 defines the tool's purpose: 'Report a problem, request a feature, or flag a wrong-looking result for THIS server'. It uses specific verbs and resources, and is distinct from all sibling data-retrieval 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?

Provides explicit usage contexts: 'Use when the user reports a bug, says a tool's output looks wrong, or wants a capability this server doesn't have.' Does not explicitly state when not to use or mention alternatives, but context is clear.

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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