Check a GitHub repository's health signals: stars, forks, open issues, license, archived/disabled status, and days since last push. Flags likely-abandoned or unlicensed repos. Useful before depending on a repo.
| Name | Required | Description | Default |
|---|---|---|---|
| repo | Yes | Repository name | |
| owner | Yes | Repository owner (user or org) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the checks performed and the flagging behavior for abandoned/unlicensed repos, but does not mention rate limits, authentication needs, or return format. It adds some behavioral context beyond the schema but lacks comprehensive disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is a single sentence that front-loads the action, lists the health signals, and ends with usage guidance. There is no redundant wording, and the structure is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with no annotations and no output schema, the description covers the purpose, the data checked, and the intended usage. It could be more explicit about the return format, but the 'flags' behavior implies a report, and the description is sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both 'owner' and 'repo' described in the input schema. The description does not add parameter-specific details beyond the schema, so the baseline 3 is appropriate—the schema already does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Check') and resource ('GitHub repository's health signals'), then enumerates the exact signals checked. It clearly distinguishes itself from sibling tools, which target URLs, domains, SSL, and web content, by being GitHub-specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear usage context with 'Useful before depending on a repo,' which tells the agent when to apply this tool. It does not explicitly name alternatives or exclusion criteria, but the sibling set makes it obvious this is the GitHub-specific health check, so guidance is adequate though not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools audit overlapping site signals (seo_audit vs structured_data_extract vs tech_stack_fingerprint; page_performance_check vs pagespeed_insights; ssl_cert_check vs ssl_labs_grade; broken_link_check vs sitemap_url_validator), so an agent could initially pick the wrong one. Descriptions usually clarify the distinction, but the boundaries are not always obvious.
Most names follow a snake_case target+operation pattern (ssl_cert_check, email_deliverability_check), but check_open_ports and check_robots_sitemap reverse the order, and the action suffixes vary widely (check, audit, validate, lookup, extract, grade, report, insights). Still readable, but not a single predictable convention.
At 29 tools, the server is above the 25-tool threshold and feels like an undifferentiated grab bag of single-purpose audits rather than a tightly scoped toolkit. Many checks could be consolidated (e.g. the separate SSL and performance tools, or domain_report versus its component checks).
For a web/domain/email/security diagnostics toolbelt, the coverage is unusually broad: DNS, TLS, email, SEO, structured data, vulnerabilities, ports, redirects, and more are all represented. Minor gaps exist (no generic HTTP request/debug tool, no zone-transfer or full WHOIS history), but agents can accomplish most diagnostic workflows without hitting dead ends.