GitHub trending repos — stars >20 + recent push, sorted by stars desc. Public GitHub Search API no-key. Momentum proxy for dev tooling / open source virality.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max repos, default 25 | |
| language | No | Filter by language e.g. TypeScript | |
| since_days | No | Pushed within N days, default 7 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool uses the public GitHub Search API without authentication, and details the filtering logic (stars >20, recent push, sort). However, it omits potential rate limits, pagination behavior, or error handling. These are useful but not critical gaps given the disclosure of key traits.
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 extremely concise with two short sentences that convey the essential information. It is front-loaded with the core purpose and immediately provides the key criteria. No extraneous text, every word earns its place.
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?
The description explains the source and criteria but does not describe the output format (e.g., what fields each repo includes) or pagination behavior. Since there is no output schema, this omission leaves the agent uncertain about the response structure. Given moderate complexity (3 parameters, no output schema), additional context on return values would improve completeness.
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 covers all three parameters with descriptions, giving 100% coverage, so the baseline is 3. The description adds value by explaining the underlying selection criteria ('stars >20 + recent push') that the parameters influence, helping the agent understand how 'limit', 'language', and 'since_days' affect results beyond their basic constraints.
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 returns GitHub trending repos with criteria of stars >20 and recent push, sorted by stars descending. It also mentions it uses the public GitHub Search API with no key required, making the purpose specific and unambiguous. While it doesn't explicitly differentiate from sibling tools like github_repo_intel, the purpose is well-defined.
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 implies usage for dev tooling and open source virality ('Momentum proxy'), but it does not provide explicit guidance on when to use this tool versus alternatives like github_repo_intel for detailed repo info. There are no when-not-to-use statements or clear context for exclusion of other use cases.
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.
Tools cover very diverse domains (weather, FDA, legal, crypto, etc.), so cross-domain confusion is low. However, within domains there is notable overlap: multiple food recall tools (food_recall_check, food_safety), multiple weather tools (weather_current_global, weather_forecast_grid, weather_alerts, weather_bias), and several Polymarket-related tools. This can cause agent misselection.
Naming is inconsistent: some tools use verb_noun (search_arxiv, scrape, validate_agent_manifest), others use noun phrases (smart_money, space_weather, tide_data), and some are long descriptive phrases (cross_platform_arb_scan, polymarket_event_scan). No single pattern is followed, making predictions difficult.
95 tools is excessively high for any coherent purpose. The server appears to be a random aggregation of APIs with no clear scope. Such a large catalog overwhelms agents and dilutes utility; most tools could be split into specialized servers.
Although many domains are touched, each is covered only shallowly. For example, weather lacks historical data, legal lacks case details beyond court opinions, and financial lacks stock prices. There are obvious gaps like no user authentication or data persistence. The tool set feels like a collection of endpoints rather than a cohesive service.