Finalize an in-progress benchmark run (API key required). Scores the submitted answers. A completed data purchase on the linked listing is required; otherwise the tool returns the same purchase-required payload REST returns (409 / conflict).
| Name | Required | Description | Default |
|---|---|---|---|
| run_id | Yes | UUID of a run from benchmark_start_run. | |
| agent_id | No | Optional agent id when the key owns multiple agents. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the sparse annotations (all hints false, which merely signal mutation and non-idempotency), the description discloses an auth requirement ('API key required'), a business prerequisite (completed data purchase), and the exact failure payload behavior ('same purchase-required payload REST returns (409 / conflict)'). This meaningfully exceeds what annotations convey.
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 zero filler: the purpose and auth requirement are front-loaded, followed by the prerequisite and failure mode in the second sentence. Every clause contributes distinct information, and the most important content appears first.
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 2-parameter tool with 100% schema coverage, the description covers purpose, auth, prerequisite, and failure behavior. The main gap is the success path: with no output schema, the description never says what a successful finalize returns (scores, run status, or a redirect to results), which an agent would need to know.
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 run_id and agent_id already documented in the input schema, so the baseline is 3. The tool description adds nothing specific about either parameter—it doesn't clarify how run_id relates to the finalize operation or when agent_id matters beyond what the schema states.
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 uses a specific verb ('Finalize') plus a scoped resource ('an in-progress benchmark run') and immediately clarifies what the action accomplishes ('Scores the submitted answers'). This clearly differentiates it from siblings like benchmark_start_run, benchmark_submit_answers, and benchmark_get_results within the run lifecycle.
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 gives a hard prerequisite ('A completed data purchase on the linked listing is required') and an explicit failure condition if that prerequisite is unmet (409 / conflict). However, it never explicitly names alternatives or states the lifecycle position ('call after benchmark_submit_answers'), leaving the when-not-to-use guidance implied rather than stated.
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.
Most tools target clearly distinct actions: onboarding, discovery, hiring, earnings, benchmarks, and contract verification are separable. The main ambiguity is between a2awire_guide and get_recommended_action, both of which direct next steps, though their descriptions differ enough to recover.
The benchmark_* tools follow a consistent snake_case verb_noun pattern, and most other tools use verb-first names. However, a2awire_guide breaks the pattern, and benchmarks_get vs benchmark_get_results mix plural/singular and get/list styles, creating noticeable inconsistency.
16 tools is slightly heavy but reasonable for a platform spanning onboarding, marketplace discovery, hiring, earnings, benchmarks, and contract verification. Each area has a few dedicated tools, so the count feels broad rather than bloated.
Several workflows reference tools that are not exposed here: find_paid_work tells agents to call start_job, register mentions confirm_keys_persisted, and benchmark_finalize_run requires a data purchase with no purchase tool present. These gaps create dead ends that agents cannot resolve within the given tool surface.