Awesome JEV
Server Details
Search Jev / System One projects and read their recorded inclusion evidence.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
- Repository
- daftAI2026/awesome-jev
- GitHub Stars
- 14
TDQS
Scored across 2 tools
The two tools split cleanly along the retrieve-one vs find-many axis: get_project fetches a single project by identity, while search_projects queries the collection. There is no overlap or plausible misselection between them.
Both names follow the same verb_noun snake_case pattern (get_project, search_projects). The verbs are precise and conventionally paired with the plural/singular noun forms, making the set highly predictable.
For a read-only public project directory, search plus fetch is the minimal viable surface, but two tools is thin — there is no separate enumeration tool for categories, tags or languages. The count is defensible yet borderline under-scoped.
Core discovery workflows are covered: keyword/category/tag/language search with bounded pagination, plus single-project retrieval with identity resolution. Minor gaps remain around enumerating available categories/tags/languages or traversing result sets beyond bounded snapshot pages.
Available Tools
2 toolsget_projectGet a projectARead-onlyIdempotentInspect
Read one public GitHub project and its inclusion evidence. Resolves known old addresses; missing or hidden identities return null.
| Name | Required | Description | Default |
|---|---|---|---|
| identity | Yes | GitHub owner/repository or https://github.com/owner/repository. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds genuinely new behavior: legacy addresses are resolved automatically and missing/hidden identities yield null, which tells the agent how to interpret failures.
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?
Two compact sentences, front-loaded with the operation and scope, followed by edge-case behavior. No filler or repetition of the name or schema.
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?
With one fully documented parameter and annotations covering the safety profile, the definition is nearly sufficient. Since there is no output schema, the mention of 'inclusion evidence' and the null-return case carries the return semantics, though the actual evidence payload is only hinted at.
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%, so the baseline is 3; the schema already defines identity as owner/repo or a GitHub URL. The description goes further by noting that identities can be stale addresses that get resolved and can be hidden, adding acceptance semantics beyond the schema's format hint.
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?
States a specific verb (read) and resource (one public GitHub project) plus the returned evidence, which is clearer than a bare name restatement. The word 'one' implicitly contrasts with the sibling search_projects, but the sibling is never named, so the differentiation is left to inference.
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 phrase 'Read one public ... project' implies a single-identity lookup versus the plural search_projects, but there is no explicit when-to-use or when-not-to-use guidance and no named alternative. Usage is inferable rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_projectsSearch Awesome JEV projectsARead-onlyIdempotentInspect
Find public Jev / System One projects by keyword, category, tag or language. Returns bounded pages from a build snapshot.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | ||
| page | No | ||
| sort | No | Default: stars. | |
| limit | No | Default: 10; maximum: 20. | |
| query | No | Plain-text words; all words must match. No regex or semantic search. | |
| category | No | ||
| language | No | Exact programming language, case insensitive. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds genuinely new context: results come as 'bounded pages from a build snapshot,' telling the agent results are paginated and may be stale relative to live data — a real behavioral disclosure beyond the structured fields.
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?
Two sentences with no filler, front-loading the core action and resource before the return-shape note. Every clause 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?
For a read-only search tool with strong annotations and no output schema, the description covers what it searches, on what facets, and that results are paginated from a snapshot. Minor gaps: no note on what a result record contains or behavior when no facet is supplied.
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?
At 57% schema coverage, the schema documents query (plain-text, no regex), sort and limit defaults, and two enums. The description maps four facets to parameters but adds nothing beyond naming them, and says nothing about page, sort, or limit behavior. Adequate but not compensating for the uncovered parameters.
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 gives a specific verb ('Find') plus resource ('public Jev / System One projects') and enumerates the matchable facets (keyword, category, tag, language). It doesn't explicitly name sibling get_project as the ID-lookup alternative, so the distinction is inferable rather than stated.
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?
Usage is only implied: you'd use this when you want to discover projects by facet rather than fetch a known one. There is no explicit when-to-use/when-not, no mention of get_project as the alternative for ID-based retrieval, and no guidance on combining facets or zero-result behavior.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
- First observed
get_project - First observed
search_projects
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