Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tikalk/adlc-team-skills --skill factory-missiongit clone --depth 1 https://github.com/tikalk/adlc-team-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tikalk/adlc-team-skills/factory-mission)<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/factory-mission"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/factory-mission/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/factory-mission"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/factory-mission.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00039 | $0.02057 |
| Opus 5.5 | $0.00016 | $0.00823 |
| Sonnet 5.5 | $0.00008 | $0.00411 |
| Haiku 4.5 | $0.00004 | $0.00206 |
Grade A, and why
factory-mission scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
- Universal Skill Routing: Decoupled step dispatching. It scans installed skills and hands the inventory to subagents (the model picks which tool fits the step).
- 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. - 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. - Self-Contained Worker Brief: The Mission Brief is persisted to
.adlc/workflows/runs/<run_id>/brief.mdas a draft. Resumed runs and cross-runtime workers read it from disk — no session-context dependency. - Worktree Isolation: Each run gets its own git worktree. Never touches the user's main checkout. Cleaned up on exit (retained if unsaved work).
- Lease-Based Liveness: The state file carries a renewable lease with heartbeat + TTL. Resume can distinguish live, stale, and completed runs.
- 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.
- 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), orcli:<runtime>(optional cross-vendor). Theagentlane is the default for unattended stages. - 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. - Workflow Memory & Self-Improvement: Persistent JSONL database (
.adlc/workflows/memory.jsonl, workspace-global) stores learnings across runs.factory-learnperiodically runs retrospectives to prune/weight memories. - Hierarchical Context Parameters: Workflows and agents reference parameters as
{{params.<key>}}, resolved from most specific to least specific:agent < workflow < repository < project < default. - Decoupled Test/Code Separation: In
autonomousorsupervisedmodes, it splitsimplementinto sequentialtest(Test Agent writes failing tests under read-onlysrc/) andcode(Implement Agent writes code under read-onlytests/) 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.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago Changed · +2 lines 29aa682dda88
- 18d ago Changed b4d7508ffaf3
- 25d ago First seen · 91 lines · 39 tokens per session scan A c063b62d3396
factory-mission is a skill published in the GitHub repository tikalk/adlc-team-skills (141 stars, last pushed yesterday), licensed MIT. It adds 39 tokens to every session and 2,057 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-21.
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