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 agentmods add skills/luisfelipemoro/harness-devkit/multi-agentnpx skills add LuisFelipeMoro/Harness-devkit --skill multi-agentgit clone --depth 1 https://github.com/LuisFelipeMoro/Harness-devkitWhat 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 | $0.00085 | $0.01215 |
| Opus 5 | $0.00043 | $0.00607 |
| Sonnet 5 | $0.00017 | $0.00243 |
| Haiku 4.5 | $0.00009 | $0.00121 |
Grade A, and why
multi-agent 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 3d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run the full multi-agent coding pipeline. If no task is provided, ask first.
Contract
- Input: a feature/epic description (ask if not provided).
- Output: implemented, tested epics with Review/Stress/QA/Verdict scores; a
[{key}]-prefixedPROGRESS.mdentry per epic; DevOps artifacts on final PRODUCTION READY; a PR fromrelease/{slug}-{key}tomain. - Boundary: Coder owns tests + implementation, written against the Architect's frozen Test Case table and falsified before handoff; Reviewer/StressTester run only after QA approval or escalation; unmitigated CRITICAL security is automatic NOT READY.
- Done when: the Pipeline Summary prints after the final epic's Verdict with Security Gate, Falsification evidence, and Coverage shown.
Model assignment (see CLAUDE.md Model assignment table): dispatch the Architect on
opus; Analyst, PM, Scrum Master, QA, Reviewer, Stress, Verdict, and the orchestrator onsonnet; the Coder (core + backend/frontend overlay), Tuner, DevOps, and any read-only Explore/mapping sub-agent onhaiku. Don't run exploration on opus or the Architect's design pass on haiku.
Phase 0 — Delivery setup (once, before planning)
Derive the delivery slug + key from the feature name, create .worktrees/dlv-{key}/ on
release/{slug}-{key}, and run everything inside it. An existing worktree for the key means
resume (read the delivery file's Status + [{key}] PROGRESS.md entries), not recreate.
Ask before the first git push. Never commit or merge to main — the terminal step is a PR
from the release branch. Commands, header block, and branch rules:
../../references/delivery-and-worktree.md.
Phase 1 — Planning (once)
Load and follow skills/planning/SKILL.md (Phase 0 through Phase 4). Phase 2 (grill-me plan stress) and Phase 3 (human validation of unresolved questions) are mandatory before any coding.
- If
docs/deliveries/{key}/product-brief.md+PRD.mdalready exist (from a prior/analysisrun for this key): load them and skip Phase 0 (inline analysis). - If the delivery file for this key already exists and was approved: skip Phases 0–2 and proceed directly to Phase 3 (Manifest).
- On changes requested during human validation: update the delivery file → re-confirm before continuing.
What ships with it
1 file 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.
- 3d ago First seen · 70 lines · 85 tokens per session scan A 3a39a2aa73b9
multi-agent is a skill published in the GitHub repository LuisFelipeMoro/Harness-devkit (10 stars, last pushed 3d ago), licensed MIT. It adds 85 tokens to every session and 1,215 once invoked, about $0.0004 per session on Opus 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…