jobstack-mcp

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description goes well beyond by disclosing the exact return envelope ({ meta, job }), the flat Job shape matching search_jobs, the critical id-format caveat (NOT prefixed with source name), the composite ATS format with a concrete example, and the error behavior for unsupported sources. This is rich behavioral context that adds real value.

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 three sentences, front-loaded with the core function, then progressively adds essential caveats. Every sentence contributes unique information (return shape, id rules, source limitations) with no filler or redundancy.

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 2-parameter, simple fetch tool with no output schema, the description covers everything an agent needs: the return shape, id semantics, ATS exception, and error behavior when a source doesn't support single-job lookup. The sibling search_jobs is referenced, and the safety profile is already in annotations. No significant gaps exist.

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 already provides 100% coverage with descriptions for both parameters, so the baseline is 3. The description adds valuable semantics beyond the schema: it emphasizes that the id is the native upstream id as returned by search results, explicitly warns against prefixing with source name, and details the ATS composite format for round-tripping. This extra context justifies a 4.

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 opens with a specific verb+resource+scope: "Fetch one job posting by its source engine and native id, returned as { meta, job } with the same flat Job shape search_jobs yields." This clearly distinguishes it from the sibling search_jobs (single vs. list) and fully conveys the tool's purpose.

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: it specifies the input (source + native id), explains the id semantics, and notes when the tool cannot be used ("Not every source supports single-job lookup — a search-only source returns a not_supported / not_found error"). However, it does not explicitly say "use search_jobs instead when you need to list jobs," so the alternative guidance is implicit rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Beyond the readOnly/idempotent/destructive annotations, the description reveals significant behavior: parallel fan-out to six sources, merging/sorting by postedDate, pagination of the combined set, and an optional 'sources_errored' map for partial failures. This is valuable context that annotations alone do not provide.

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 one dense but well-organized paragraph. The first sentence states the core purpose, and each subsequent sentence earns its place by covering sources, merge/sort/pagination, the Job shape, the response envelope, and usage tip. No filler or redundancy.

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 no output schema, the description fully specifies the Job fields and the response envelope (meta, sources_errored, total, count, limit, offset, results), along with error behavior. This gives an agent everything needed to interpret the result. Combined with the strong annotations, this is complete for a complex search tool.

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 already covers all parameters with detailed descriptions. The description adds meaning by explaining that limit/offset apply to the merged set after sorting by postedDate, and clarifies the 'sources' parameter's role in restricting fan-out. This context helps interpret pagination and filtering semantics beyond the schema.

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 opens with a specific verb+resource: 'Search job postings across every configured source and merge the results into one flat Job shape.' It clearly distinguishes from the sibling tool get_job, which presumably retrieves a single job, by emphasizing the unified multi-source feed.

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 states when to use the tool (search across all sources) and gives basic guidance ('Use sources= to restrict to specific engines'). However, it does not explicitly say when not to use it or direct users to get_job for single-job lookups, so it lacks an explicit alternative mention.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.