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devtune_get_agent_picks_starter_test

Read-onlyIdempotent

Read the project's Agent Picks starter test as it runs, run by run. test is the project's latest starter test, or null when it has none (then runs and tools are empty). test.status is queued, running, completed, failed or cancelled; planned_runs counts the runs it queued and completed_runs those with status completed. A failed or cancelled test keeps its runs, so report what its completed runs picked and that the rest did not finish. Each run gives the request it was given (intent add = build it, recommend = recommend one, hosted = hosted service, and request the text), its agent and model, its status, and sandbox_attempts, the sandboxes it started. outcome is null until the run is classified, then installed (tool_key names the tool), built_its_own (the agent wrote its own), no_provider (wired in a hosted service without naming a provider), other_tool (other_tools lists the packages and hosts it added that no tool in the test names), none or unclassified. tools lists the tools the test ran with and gives the display name for each tool_key; it is null for a test queued before tests recorded their tools, so do not report which tools such a test compared. stage is sandbox, setup, agent or judging while running, otherwise null, including older runs. During agent, model_calls and model_spend_usd report proxy-recorded activity across attempts; null means no meter was recorded. model_spend_incomplete marks a lower bound, not a final bill. These are live per-run results, not rates: for install rates with their likely ranges, read devtune_get_agent_picks_summary. It shows the latest completed non-directional own test first, otherwise the latest completed directional own test, including a starter. A starter never displaces a full own result or feeds loss Actions, re-test baselines or trends.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior5/5

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

Annotations already cover read-only/idempotent/non-destructive, and the description goes well beyond them: null semantics for test/tools/model_calls, freshness ('live per-run results, not rates'), stage lifecycle values, and the caveat that model_spend_incomplete marks a lower bound rather than a final bill. These edge-case disclosures materially change how an agent should interpret and report the data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded, but the body is a single dense ~250-word paragraph mixing request semantics, outcome enums, tool_key explainers and spend caveats with no bullets or headings. Much of the content is necessary absent an output schema, but the run-on structure hurts scannability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the full burden of explaining return values and does so comprehensively: every field (test, runs, outcome, tools, stage, model_calls, model_spend_usd) is defined including its null/edge-case behavior. An agent has what it needs to call and interpret the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters and the schema is empty, so there is nothing for the description to disambiguate; baseline 4 applies. No missing parameter meaning is a gap here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific verb and resource: 'Read the project's Agent Picks starter test as it runs, run by run,' and distinguishes the starter-test concept from a full own test. It does not explicitly route against the closest siblings (devtune_get_agent_picks_test, devtune_get_agent_picks_run), which is the only thing keeping it from a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It names an alternative with a clear condition: 'for install rates with their likely ranges, read devtune_get_agent_picks_summary,' and adds a constraint ('a starter never displaces a full own result or feeds loss Actions, re-test baselines or trends'). No explicit when-to-prefer-this-over get_agent_picks_test/run, so it stops short of 5.

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

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