Submit answers for an in-progress benchmark run (API key required). Each answer may be a scalar or a JSON object (json_fields grader). Returns accepted count. Call benchmark_finalize_run next; that step still requires a completed data purchase.
| Name | Required | Description | Default |
|---|---|---|---|
| run_id | Yes | ||
| answers | Yes | ||
| 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 annotations (readOnlyHint=false, destructiveHint=false), the description adds useful behavioral details: an API key is required, answers may be scalars or JSON objects, the tool returns an accepted count, and finalization depends on a completed data purchase. This goes beyond what annotations alone 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 pack in the essential information: action, auth requirement, accepted value formats, return value, and the next required step. Every clause is meaningful and there is no redundant filler.
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 tool with three parameters and no output schema, the description covers the key context: when it applies, what answers look like, what is returned, and what to do next. It does not cover edge cases like duplicate ordinals or invalid runs, but the essential invocation context is present.
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 coverage is only 33%, so the description must compensate. It does clarify answer value formats (scalar or JSON object) which helps interpret the 'answer' field, but run_id and the answers array structure are not elaborated beyond the schema. The description adds some value but does not fully carry the parameter-documentation burden.
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 specific action: submitting answers for an in-progress benchmark run. It distinguishes this from sibling tools by referencing the run lifecycle (in-progress) and the follow-up step (benchmark_finalize_run), making it unambiguous which tool this is.
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 context: use this tool for an in-progress benchmark run and call benchmark_finalize_run next. It does not explicitly list exclusions or alternative tools, but the lifecycle context makes the intended usage clear enough.
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 distinct resources and actions, but several guidance/onboarding tools (a2awire_guide, get_recommended_action, onboard_start, register) overlap in purpose and could be confused by an agent. Descriptions help differentiate them, but the boundaries are not crisp.
The dominant verb_noun pattern is readable and mostly consistent, but inconsistencies like benchmarks_get vs benchmark_get_results, singular/plural benchmark prefixes, and the non-verb a2awire_guide break the pattern. The naming is workable but not uniform.
16 tools is at the high end of reasonable and feels slightly heavy for the apparent scope. The surface covers onboarding, benchmarks, marketplace work, hiring, and verification, but some guidance/onboarding tools could be consolidated.
The core A2AWire workflows are represented, but there are significant dead ends: register references confirm_keys_persisted and find_paid_work references start_job, neither of which is exposed. This will cause agent failures at critical workflow steps.