Agent skill

Factory Mission

by tikalk in tikalk/adlc-team-skills

A skill your agent uses when executing a spec-gated mission from the queue — inner loop specify → plan → implement ↔ converge with tracker integration, worktree isolation, and a circuit breaker.

MITAuto-check passedDevelopment

Install Factory Mission

skills CLI
$ npx skills add tikalk/adlc-team-skills --skill factory-mission -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install tikalk/adlc-team-skills factory-mission --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/tikalk/adlc-team-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/factory/factory-mission .claude/skills/factory-mission && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
factory-mission
GitHub stars
141
Token cost
~2.2k tokens
SKILL.md length
1,103 words
Files
7 (incl. references)
Skills in repo
44
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when executing a spec-gated mission from the queue — inner loop specify → plan → implement ↔ converge with tracker integration, worktree isolation, and a circuit breaker.

  • Works in 3 steps: to 4: Setup & Compilation → Executing the Converge Loop → Completion & Write-Back
  • Executing a spec-gated mission from the queue — inner loop specify → plan → implement ↔ converge with tracker integration
  • SKILL.md covers What this skill does, When to use and Process
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Factory Mission is an agent skill from tikalk/adlc-team-skills. Use when executing a spec-gated mission from the queue — inner loop specify → plan → implement ↔ converge with tracker integration, worktree isolation, and a circuit breaker.

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `mission-template.yml`, `references/agent-integrations.md` and `references/executor.md`).

It sits in Development, covering Git worktrees. The repository describes itself as: Agent skills for the Agentic SDLC: team lifecycle (team-boot, team-learn, team-init, team-repair), software factory, evals, CDR lifecycle with confidence scoring, and… The licence is MIT.

When your agent uses it

  • Executing a spec-gated mission from the queue — inner loop specify → plan → implement ↔ converge with tracker integration
  • Worktree isolation
  • A circuit breaker

Example prompts

  • “/factory-mission”

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. to 4: Setup & Compilation
  2. Executing the Converge Loop
  3. Completion & Write-Back

What it can do on your machine

Read from SKILL.md and the folder at commit 4c4ad44. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Factory Mission loads about 2.2k tokens when it runs, and up to ~15k if it reads all its reference files. Until then it costs about 48 tokens; SKILL.md has 1,103 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~48
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~15k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from tikalk/adlc-team-skills at commit 4c4ad44, republished under its MIT licence (© tikalk). 1,103 words, ~2,196 tokens.

Download SKILL.mdSave it as .claude/skills/factory-mission/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
factory-mission
description
Use when executing a spec-gated mission from the queue — inner loop specify → plan → implement ↔ converge with tracker integration, worktree isolation, and a circuit breaker.

factory-mission

What this skill does

factory-mission is the execution-harness orchestrator of the software factory. It takes a feature description, structures it into a Mission Brief (goal, constraints, non-goals, success criteria), generates an ordered step list, and executes those steps via sequential subagent runs.

It implements the following key factory platform capabilities:

  1. Universal Skill Routing: Decoupled step dispatching. It scans installed skills and hands the inventory to subagents (the model picks which tool fits the step).
  2. Tracker-Agnostic Integration (references/tracker-integration.md): When invoked with --issue <ref>, it pulls ticket context, respects automation/dispatch labels (autonomous/supervised), and writes back status comments + iteration logs.
  3. Inter-Agent Comment Bus (references/tracker-integration.md §Inter-Agent Comment Bus): When tracker-integrated, each step's terminal output (decisions, findings, artifact references — never drafts) is published as a structured comment on the PR/MR/issue. The next step reads previous markers before starting. This is the durable inter-agent memory that survives session boundaries, runtime switches, and pod crashes. Drafts stay on local disk.
  4. Self-Contained Worker Brief: The Mission Brief is persisted to .adlc/workflows/runs/<run_id>/brief.md as a draft. Resumed runs and cross-runtime workers read it from disk — no session-context dependency.
  5. Worktree Isolation: Each run gets its own git worktree. Never touches the user's main checkout. Cleaned up on exit (retained if unsaved work).
  6. Lease-Based Liveness: The state file carries a renewable lease with heartbeat + TTL. Resume can distinguish live, stale, and completed runs.
  7. Stall Detection: After dispatching a subagent, observable progress is checked at a configurable window (default 20 min). A hung agent that passes the circuit breaker is detected and killed.
  8. Lane-Based Dispatch (references/lanes.md): Steps can run on different lanes — inline (this session), agent (fresh session of same CLI for maker/checker separation), or cli:<runtime> (optional cross-vendor). The agent lane is the default for unattended stages.
  9. Scratchpad Tools: Subagents share named, run-private scratchpads (.adlc/workflows/runs/<run_id>/scratchpads/<name>.txt) to compile notes, drafts, and reviews incrementally before publishing.
  10. Workflow Memory & Self-Improvement: Persistent JSONL database (.adlc/workflows/memory.jsonl, workspace-global) stores learnings across runs. factory-learn periodically runs retrospectives to prune/weight memories.
  11. Hierarchical Context Parameters: Workflows and agents reference parameters as {{params.<key>}}, resolved from most specific to least specific: agent < workflow < repository < project < default.
  12. Decoupled Test/Code Separation: In autonomous or supervised modes, it splits implement into sequential test (Test Agent writes failing tests under read-only src/) and code (Implement Agent writes code under read-only tests/) runs — each closed by a mandatory mechanical gate (see Phase 5): the RED gate proves the new suite fails before coding starts; the GREEN gate proves it passes before converge is reached.

When to use

  • "Build this feature end to end" inside a factory-enabled team.
  • You want an execution loop with a circuit breaker, score-regression checking, and a robust resume mechanism (factory-mission --resume).
  • You want to run autonomously against a ticket queue.

When NOT to use:

  • For non-factory standalone projects (run adlc-cli workflow run <workflow.yml> — the CLI engine, ADR-395).
  • Trivial 1-line changes (do them directly).

Process

factory-mission executes in alignment with the shared executor contract (references/executor.md) and the tracker-agnostic layer (references/tracker-integration.md).

Phase 0 to 4: Setup & Compilation
  1. Read the run's mission.yml (.adlc/workflows/runs/<run_id>/mission.yml). Resolve execution and supervision.
  2. If --issue <ref> is specified:
    • Discover credentials and MCP/CLI tools (references/tracker-integration.md).
    • Pull the issue content as the primary Brief description.
    • Read the labels. If dispatch is interactive or gating is human-required -> HALT execution (hand back to interactive session).
    • The comment bus is active for this run — step outputs will be published as marker comments on the PR/MR/issue.
  3. If no issue: read spec description from arguments. The comment bus is inactive — steps communicate through local files only.
  4. Structure the Mission Brief (Goal, Constraints, Non-Goals, Success Criteria). The Brief is a draft — not published to the comment bus.
  5. Resolve hierarchical Context Parameters from agent < workflow < repository < project < default and embed the frozen value map in the brief.
  6. Generate the step list based on route classification (spec, change, quick). Each step declares output_type (draft/decision/findings/artifact-ref) and reads_from (markers or local paths) per the executor contract.

Team index fallback: when no team record-class index was injected at session start, read the binding records directly from docs/adlc/memory/ (ADR-401 dual-read order: docs/adlc/memory first, legacy .adlc/memory fallback) and state that fallback in one line. Never block on the missing injection.

Show full SKILL.md (403 more words)Show less
Phase 5: Executing the Converge Loop

Execute steps sequentially. When reaching implement / converge:

Decoupled Test/Code Execution (mandated TDD)

In autonomous and supervised modes, the implement step is split into two sequential subagent dispatches, each closed by a mechanical verification run:

  1. The Test Agent (test step):
    • Instruction: Write a failing test suite based on spec.md in tests/.
    • Enforcement: Mount src/ as hard read-only; only tests/ is writeable.
    • RED gate (mandatory): the executor runs the suite and asserts at least one test FAILS. A suite that passes immediately means the feature already exists or the tests assert nothing — route to SPEC_CORRECTION_NEEDED with the run output; never proceed to the code step. Record the failing count in the run log.
  2. The Implement Agent (code step):
    • Instruction: Write minimum implementation code in src/ to pass the tests.
    • Enforcement: Mount tests/, spec.md, and plan.md as hard read-only; only src/ is writeable.
    • GREEN gate (mandatory): the executor runs the suite again; converge is never reached with a red suite. Any failure loops straight back to the code step with the failure list attached (this loop-back does not consume the converge circuit breaker; only broken iterations do — use the code-step retry cap from mission.yml).

Skipping the split is allowed only when the run declares no test surface: tdd: false in mission.yml, a docs/config-only step, or interactive mode (the attended pair runs its own discipline — e.g. superpowers' test-driven-development). A code-bearing step in autonomous/supervised mode never skips it.

Converge Loop (Implement ↔ Converge)
  1. Execute implement step (or test + code steps — RED→GREEN gates enforced first).
  2. Execute converge step (independent judge mode; checks against Brief and Non-Goals).
  3. If converge returns:
    • DONE (and quality is above quality_threshold): Loop exits.
    • CONTINUE: Increment consecutive_tasks_appended. Check circuit breaker (default 3) and score-regression counter. Repeat.
    • SPEC_CORRECTION_NEEDED: Stop and route to Phase 6.
Phase 6: Completion & Write-Back
  1. If tracker-integrated: read all marker comments from the PR/MR/issue to compile the audit trail (converge decisions, test findings, implement artifact references, convergence history).
  2. Close the shared run: final adlc-cli workflow state advance <run_id> --step <last> --status completed (the run dir is the durable archive; no separate move).
  3. Write per-implement logs to iterations.md.
  4. If tracker-integrated:
    • Post completion summary as a ticket comment (marker: factory-mission:status=completed:run=<run_id>).
    • Transition lifecycle label from executing to validation (or done if merged).
    • Stamp agent-authored on opened PRs.
    • Defer PR merge to code-owner approval (never auto-merge without approval).
  5. Output the complete audit summary.

© tikalk, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (references) in skills/factory/factory-mission of tikalk/adlc-team-skills.

  • SKILL.md
  • mission-template.yml
  • references/agent-integrations.md
  • references/executor.md
  • references/lanes.md
  • references/mission-brief-template.md
  • references/tracker-integration.md

Open the folder on GitHubat commit 4c4ad44

Compare with similar skills

Factory Mission next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Factory Mission compared with similar skills
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Finishing A Development Branchfarm-fe/farm5.6k34 repos~1.8kAutomated safety check: PassMIT
Git Worktree Cleanuplobehub/lobehub83k—~2.8kAutomated safety check: PassCustom licence
Keep Codex Fastvibeforge1111/keep-codex-fast1.6k—~3.1kAutomated safety check: PassMIT

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Categories

Questions about Factory Mission

What does Factory Mission do?

A skill your agent uses when executing a spec-gated mission from the queue — inner loop specify → plan → implement ↔ converge with tracker integration, worktree isolation, and a circuit breaker. Factory Mission is an agent skill from tikalk/adlc-team-skills. Use when executing a spec-gated mission from the queue — inner loop specify → plan → implement ↔ converge with tracker integration, worktree isolation, and a circuit breaker.

When should I use Factory Mission?

Factory Mission fits situations like: executing a spec-gated mission from the queue — inner loop specify → plan → implement ↔ converge with tracker integration; worktree isolation; A circuit breaker.

How do I install Factory Mission in Claude Code?

Run `npx skills add tikalk/adlc-team-skills --skill factory-mission -a claude-code`. Or copy the skill folder (skills/factory/factory-mission in tikalk/adlc-team-skills) into .claude/skills/factory-mission in your project. Claude Code loads it when a task matches its description.

How do I install Factory Mission in Codex?

Run `npx skills add tikalk/adlc-team-skills --skill factory-mission -a codex`. Or copy the skill folder (skills/factory/factory-mission in tikalk/adlc-team-skills) into .agents/skills/factory-mission in your project. Codex loads it when a task matches its description.

Can I use Factory Mission in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add tikalk/adlc-team-skills --skill factory-mission -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/factory-mission, .gemini/skills/factory-mission, .github/skills/factory-mission and .opencode/skills/factory-mission in your project.

What does Factory Mission need to run?

SKILL.md names no scripts, command-line tools or credentials: Factory Mission is instructions for the agent only.

Does Factory Mission access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Factory Mission safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Factory Mission use?

Factory Mission is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Factory Mission use?

About 2.2k tokens (SKILL.md is roughly 8.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 13k tokens, read only when the agent opens those files.

What are the alternatives to Factory Mission?

Skills that share tags, products or a category with Factory Mission: Finishing a Development Branch (obra/superpowers, 297k stars), Migrate Core Code to Submodules (tinyhumansai/openhuman, 42k stars), Finishing A Development Branch (farm-fe/farm, 5.6k stars) and Git Worktree Cleanup (lobehub/lobehub, 83k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Factory Mission?

tikalk (a GitHub organization) maintains it in tikalk/adlc-team-skills, which has 141 GitHub stars. The repository holds 44 skills in this directory. The repository was last updated on October 8, 2026.

Source: tikalk/adlc-team-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.