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evolve_apply

Implement a promoted format-evolution suggestion by editing render_brief, adding tests, and opening a pull request.

Instructions

Implement a PROMOTED + not-yet-applied format-evolution suggestion.

Spawns an evolve_applier child that: edits render_brief() in threadkeeper/brief.py to make the change; adds/extends a GOLDEN test asserting the new behavior appears AND the existing brief still renders; runs the FULL suite (.venv/bin/python -m pytest -q) until green; then opens a PULL REQUEST on a feature branch via gh — it NEVER pushes or commits to main (a human reviews + merges).

applied=1 is set ONLY when the child reports a real PR back via evolve_mark_applied — opening the PR is the autonomy gate.

Rejects ids that don't exist or aren't promoted+unapplied. Single-flight: refuses while another applier child is in flight. Returns a status line (spawned … / applier_running … / ERR …). Get ids from evolve_review().

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
evolve_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully discloses behavior: spawns child that edits specific file, runs tests, opens PR, never pushes to main, sets applied only on successful PR, and returns status. It covers rejection and single-flight.

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

Conciseness4/5

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

The description is detailed but well-structured, with clear sections for action, child behavior, constraints, and source of ids. It is front-loaded and not verbose, though slightly longer than necessary.

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?

Given the complexity (spawning a child with multiple steps), the description covers the entire process, including the return value format and references to other tools. The existence of an output schema is noted, and the description provides sufficient context.

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 only parameter evolve_id has no schema description (0% coverage), but the description adds meaning: id must be promoted+unapplied, and rejects invalid ids. This compensates well, though it could explicitly state 'evolve_id is the ID of a promoted suggestion from evolve_review'.

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

Purpose5/5

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

The description starts with a clear specific verb+resource: 'Implement a PROMOTED + not-yet-applied format-evolution suggestion.' It distinguishes from siblings like evolve_review and evolve_mark_applied by detailing the unique action of spawning an applier child.

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?

The description states 'Get ids from evolve_review()' implying when to use it, and lists constraints: id must exist and be promoted+unapplied, and single-flight rule. It does not explicitly list alternatives but context is sufficient.

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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