search_repositories
Find watched repositories whose name contains a string, with their current readings. Use it to discover what is covered before calling the other tools.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes |
Find watched repositories whose name contains a string, with their current readings. Use it to discover what is covered before calling the other tools.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes |
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 states what the tool does, but omits details such as whether the search is case-sensitive, how the 'limit' parameter affects results, what happens when no matches are found, or whether it is read-only (though 'find' implies no mutation). The description does not contradict annotations (none exist), but it lacks richer behavioral context.
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 description is two sentences, front-loaded with the primary action and purpose. Every sentence contributes value: the first defines what it does, the second gives usage guidance. There is no wasted text or repetition of schema details.
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 search tool with 2 parameters and no output schema, the description is mostly complete. It explains the purpose, the search criterion, and provides guidance on when to use it. It does not describe the return format or limit behavior, but these are not critical for a discovery tool. The absence of annotations is mitigated by the tool's inherently read-only nature implied by 'find'.
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?
The input schema has 2 parameters (query, limit) with no descriptions in the schema itself (schema description coverage 0%). The description adds meaning to 'query' by explaining that it matches a string against repository names ('whose name contains a string'). However, the 'limit' parameter is not mentioned, so the description only partially compensates for the low schema coverage.
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 clearly states the tool's function: 'Find watched repositories whose name contains a string, with their current readings.' It specifies the verb (find), resource (watched repositories), and the output (current readings). It also distinguishes itself from siblings by positioning it as a discovery step: 'Use it to discover what is covered before calling the other tools.'
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?
The description provides clear usage context: 'Use it to discover what is covered before calling the other tools.' This tells the agent when to use this tool (as a precursor to other tools). It does not explicitly mention alternatives or exclusions, but it gives a practical recommendation that is sufficient for a search tool.
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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Each tool targets a distinct query type: package status, stack review, provider incidents, model pricing, watchlist changes, etc. Even similar-sounding tools like check_package and check_stack are clearly differentiated by granularity (single package vs. whole manifest). The descriptions further remove ambiguity.
All names use lowercase snake_case, but the pattern is mixed: some are imperative verb_noun (check_package, find_model, watch_add) while many are noun phrases (advisory_severity, provider_incidents, runtime_deadlines). This is readable but not a consistent verb_noun style, so there is noticeable inconsistency.
At 31 tools, the count exceeds the 'too many' threshold (25+). While the domain is broad, the agent must navigate a large surface with many similarly scoped utilities, making selection harder. A more consolidated set (e.g., grouping related readings) would improve appropriateness.
The tool surface covers a wide range of supply-chain intelligence: package advisories, provider status, model pricing, runtime EOL, and watchlist changes. The only notable gap is lifecycle management for the private watchlist (e.g., no watch_remove or watch_list), but the overall coverage is strong.