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repo-task-proof-loop

Spec driven skill with subagents spawning

Install / Use

npx skills add DenisSergeevitch/repo-task-proof-loop

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

69/100

Category

Automation

Supported Platforms

Claude Code
OpenAI Codex

Our assessment of repo-task-proof-loop

repo-task-proof-loop scores 69/100 on our quality scale, 1502nd of 1,753 Automation skills we index.

Its SKILL.md is 15 KB long, well organised into 14 sections with 4 code examples: a thorough specification that gives an agent plenty to work with.

It has no GitHub stars yet, so there is no community track record; judge it on its content.

Substance
30/30
Structure
20/20
Description
8/15
Adoption
0/20
Freshness
11/15

Maintenance, license and trust

  • The repository was last updated about 6 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
  • Our last check on 2026-09-27 found the source still online.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 78/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

repo-task-proof-loop compared with similar skills

All 4 of these similar skills score higher than repo-task-proof-loop; compare them before choosing.

SkillScoreStarsUpdatedFormat
repo-task-proof-loop (this skill)by DenisSergeevitch6906mo agoSKILL.md
Agent-Reachby Panniantong10085.7k12d agoCLAUDE.md
headroomby headroomlabs-ai10073.9ktodayCLAUDE.md
rufloby ruvnet10073.4ktodayCLAUDE.md
crawl4aiby unclecode10084.4k2d agoMCP Server

Frequently asked questions

How do I install repo-task-proof-loop?
Run npx skills add DenisSergeevitch/repo-task-proof-loop. The install tabs above show the steps for each supported agent.
Which AI agents does repo-task-proof-loop work with?
It is written for Claude Code and OpenAI Codex, as a SKILL.md file. Other agents that read the same format can often use it too.
Is repo-task-proof-loop safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 78/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is repo-task-proof-loop still maintained?
The repository was last updated about 6 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.

name: repo-task-proof-loop description: Repo-local workflow skill for large coding tasks. Initializes .agent/tasks/TASK_ID artifacts, installs project-scoped Codex and Claude subagents, updates AGENTS.md plus the repo's Claude guide file with the workflow, and runs a spec-freeze → build → evidence → verify → fix loop with fresh-session verification. license: Apache-2.0 compatibility: Skills-compatible coding agents. Integrates with Codex and Claude Code project-scoped subagents. Bundled scripts require Python 3.10+. metadata: author: OpenAI version: "1.0.0"

Repo Task Proof Loop

Use this skill when the user wants a repeatable, auditable implementation workflow for a non-trivial coding task, especially a feature, refactor, migration, or bug fix that should leave repo-local proof in .agent/tasks/<TASK_ID>/.

All task artifacts created by this workflow must stay inside the repository.

When the examples below mention scripts/task_loop.py, that path is relative to this skill root. Run it while your shell working directory is inside the target repository.

What this skill does

  1. Initializes a strict repo-local task folder under .agent/tasks/<TASK_ID>/
  2. Seeds or updates the required artifact files
  3. Installs project-scoped Codex and Claude subagent templates into .codex/agents/ and .claude/agents/
  4. Updates the repo-root AGENTS.md Codex baseline plus the repo's Claude guide file (CLAUDE.md or .claude/CLAUDE.md) with a managed block that explains the workflow
  5. Guides the agent through a strict loop:
    • spec freeze
    • builder implementation
    • evidence packing
    • fresh verification
    • minimal fix
    • fresh verification again until PASS

See:

  • references/REFERENCE.md
  • references/COMMANDS.md
  • references/SUBAGENTS.md
  • references/SCHEMAS.md

Commands this skill supports

Treat the following words as commands when the user invokes this skill:

  • init <TASK_ID>: create .agent/tasks/<TASK_ID>/, install or refresh subagent templates, and update AGENTS.md plus the repo's Claude guide file
  • freeze <TASK_ID>: create or refine spec.md from the user task, task file, and repo guidance
  • build <TASK_ID>: implement the task against the frozen spec
  • evidence <TASK_ID>: create or refresh evidence.md, evidence.json, and raw artifacts without changing production code
  • verify <TASK_ID>: run a fresh verifier pass and write verdict.json, plus problems.md when needed
  • fix <TASK_ID>: apply the smallest safe fix set from problems.md, then refresh the evidence bundle
  • run <TASK_ID>: execute the full loop from spec freeze through verification
  • status <TASK_ID>: summarize current artifact status

If the user does not supply a command, infer the next step from repo state:

  • If the task folder does not exist, run init first. If the user clearly wants initialization only, stop there. Otherwise, after init succeeds and .agent/tasks/<TASK_ID>/spec.md exists, continue by re-evaluating repo state in the same turn. Do not overlap init with freeze, build, evidence, verify, fix, validate, status, or subagent work.
  • If spec.md is missing or placeholder-only, do freeze
  • If implementation is not yet complete, do build
  • If evidence is stale or missing, do evidence
  • If no fresh verdict exists, do verify
  • If verdict is not PASS, do fix

Initialization step

Run the bundled initializer from the repository root or current working directory inside the repo:

scripts/task_loop.py init --task-id <TASK_ID>

Optional task seeding:

scripts/task_loop.py init --task-id <TASK_ID> --task-file path/to/task.md
scripts/task_loop.py init --task-id <TASK_ID> --task-text "User task text"

The initializer will:

  • resolve the repo root
  • create .agent/tasks/<TASK_ID>/
  • create all required artifacts, including placeholders under raw/
  • install project-scoped subagent files
  • insert or refresh managed workflow blocks in AGENTS.md and the repo's Claude guide file

For Codex, the initializer keeps its managed workflow block in the repo-root AGENTS.md. Codex also supports AGENTS.override.md and configured fallback guide filenames; nested files closer to the code still take precedence, and this skill intentionally does not overwrite them. If init creates or rewrites AGENTS.md during a running Codex session, start a new Codex session before relying on the updated instructions. Codex snapshots project-doc guidance at session start.

For Claude Code, the initializer keeps its managed workflow block in the repo-root CLAUDE.md. Claude Code also supports .claude/CLAUDE.md, .claude/rules/*.md, and CLAUDE.local.md, but this skill treats root CLAUDE.md as the primary project guide because Claude surfaces it directly.

In Claude Code, if init just wrote or refreshed .claude/agents/* during the current session, do not assume those updated agents are already available mid-session.

Treat init as a serial prerequisite. Never overlap it with freeze, build, evidence, verify, fix, validate, status, or child-agent spawning.

Heavy-task default workflow

For large tasks, keep the user-facing request simple. In Codex, continue serially unless the user explicitly asks for delegation or parallel agent work; after that authorization, the skill can choose the internal child setup automatically when the current product surface supports delegation and the task shape warrants it.

Preferred delegated sequence

  1. Run init <TASK_ID> if needed. Wait for it to finish, then confirm .agent/tasks/<TASK_ID>/spec.md and the repo-local task structure exist before continuing.
  2. Only after init completes, spawn exactly one spec-freezer subagent and wait for it
  3. Spawn exactly one builder subagent and let it implement
  4. Continue with the same builder session for evidence packing
  5. Spawn exactly one fresh verifier subagent and wait for it
  6. If verdict is not PASS, spawn exactly one fixer subagent
  7. Spawn one fresh verifier subagent again
  8. Repeat steps 6-7 until the verifier returns PASS or the user stops the loop

Codex adaptive fan-out

Use this only after the user has explicitly authorized Codex delegation and the task is broad enough to benefit from bounded parallel work. Use the simpler serial sequence above for narrow tasks.

Good fits:

  • multiple independent codebase questions must be answered before the spec is stable
  • implementation can be split into disjoint write scopes
  • proof requires several independent read-only checks across different surfaces

Codex pattern:

  1. init stays serial.
  2. If the task is still ambiguous, fan out up to 3 built-in explorer children in parallel. Give each one a single question, subsystem, or path scope. Wait for them, then freeze the spec.
  3. Spawn one spec-freezer child and wait for it.
  4. Spawn one task-builder child as the integration owner.
  5. If implementation splits cleanly, the parent may also spawn bounded built-in worker children in parallel. Each worker must have explicit file or module ownership and must not write evidence.md, evidence.json, verdict.json, or problems.md.
  6. Use send_input or the equivalent follow-up surface to keep the integration builder alive for evidence packing. The builder remains the single owner of the evidence bundle.
  7. If extra proof is needed, the parent may fan out a small bounded set of read-only explorer children to rerun disjoint checks or inspect separate proof gaps in parallel. Those children may report commands, outputs, and findings, but they do not write verdict.json.
  8. Run exactly one fresh verifier child for each verify pass.

Platform behavior

  • In Codex, keep the normal path serial and auto-mode-first after init. Avoid surfacing delegation internals unless they materially affect the work.
  • In Codex, spawn bounded subagents only when the user explicitly asks for sub-agents, delegation, or parallel agent work.
  • In Codex, once delegation is authorized, the skill may choose the matching child roles and whether to stay one-child-at-a-time or use bounded fan-out. The user should not need to name specific child roles or slash commands.
  • In Codex, child spawning is still an explicit parent-orchestrator action. If the current Codex surface blocks delegation, say so briefly only when it materially affects the work, then continue serially.
  • In Codex, keep the task tree shallow. The parent session should spawn research, builder, fixer, and verifier children directly instead of asking one custom task child to orchestrate more children.
  • In Codex, once delegation is authorized, choose between one-child-at-a-time delegation and bounded fan-out from the frozen spec, repo shape, and current delegation surface. Keep init, evidence ownership, and every verifier pass serialized either way.
  • In Codex, keep helper fan-out modest and wave-based. Prefer up to 3 parallel helper children at once, wait for that wave to finish, then decide the next phase.
  • In Codex, built-in explorer is the first choice for read-only repo discovery and proof probes. Built-in worker is appropriate for bounded disjoint implementation or check reruns when you can assign explicit ownership.
  • In Codex, reuse the live builder child for evidence packing by sending it a follow-up instruction. Verifier passes must use a fresh child or fresh session; do not satisfy verifier freshness by resuming an earlier verifier. Builder and fixer children can be reused or resumed when you intentionally want that context back.
  • In Codex, inspect the current child-thread list before reusing or resuming a child. Use /agent in Codex CLI or any equivalent child-thread inventory surface available in the current Codex product surface.
  • In Codex, the plan/todo checklist UI from update_plan is optional session guidance only. It is useful for live progress display, but it is not the source of truth for this workflow.
  • In Claude Code, the skill should decide whether to stay on the main thread or let the main Claude session auto-delegate the current phase to a matching built-in or project subagent after init. The user should not need to request a specific Claude subagent or delegation mode separately.
  • In Claude Code, TodoWrite or the visible task/todo UI is optional session-scoped progress display only. It can help with live tracking in the current session, but it is not the source of truth for this workflow.
  • In Claude Code, prefer the installed project subagents from .claude/agents/, with descriptions written as proactive trigger conditions for the matching proof-loop phase. Claude's main session routes by the task request, subagent descriptions, and current context, so keep each phase prompt clear in natural language. Reuse the same builder child for the evidence step by default. Only run a fresh builder in evidence-only mode if the original builder session is unavailable or you intentionally discarded it. If init just refreshed .claude/agents/* during the current Claude session, fall back to the main thread or already-visible agents instead of assuming the refreshed ones are available immediately.
  • In Claude Code, keep the orchestration flat: main-session auto-delegation is fine, but the proof-loop workflow agents themselves are leaf roles. The parent session should own the proof-loop phase transitions instead of asking one custom task agent to spawn another.
  • In Claude Code, the canonical durable state is always the repo-local artifact set under .agent/tasks/<TASK_ID>/, especially spec.md, evidence.md, evidence.json, verdict.json, and problems.md.
  • If subagents are unavailable, preserve the same role separation across separate sessions or clear mode changes in the current session.

Use the exact role prompts from references/COMMANDS.md.

Spec freeze requirements

spec.md must contain at least:

  • original task statement
  • explicit accep

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars0
CategoryAutomation
Updated5mo ago
Forks0

Trust signals

78/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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