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/epicsagas/epic-harness/_dispatchnpx skills add epicsagas/epic-harness --skill _dispatchgit clone --depth 1 https://github.com/epicsagas/epic-harnessWhat 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 | $0.00026 | $0.02792 |
| Opus 5 | $0.00013 | $0.01396 |
| Sonnet 5 | $0.00005 | $0.00558 |
| Haiku 4.5 | $0.00003 | $0.00279 |
Grade A, and why
_dispatch scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Dispatch Engine
CRITICAL: When accessing harness data, run HARNESS_DIR=$(epic-harness path) first. NEVER use .harness/ in the project directory.
You have access to the following skills. Invoke the matching skill BEFORE responding or taking action. Even a 1% chance of relevance means you should invoke it.
Dispatch Rules
| Context Signal | Invoke Skill |
|---|---|
| New feature implementation starting | tdd |
| Test failure, error, or unexpected behavior | debug |
| Auth, DB, API, infra, or secrets code touched | secure |
| Loops, queries, rendering, or data processing code | perf |
| File > 200 lines or high cyclomatic complexity | simplify |
| Public API/function added or changed | document |
| Before completing /go or /ship | verify |
| User wants to commit changes | commit |
| Context window > 70% used | context |
| User request is vague, unfocused, or presents a solution without a clear problem | discover |
| User shares code for review, mentions code smells, or asks to refactor/analyze | episteme → analyze_code + suggest_refactorings → feed results into go:plan mode |
User invokes /reflect, asks about AI usage quality, "am I using AI well", "thought amplifier", or requests AI usage self-assessment |
reflect |
| Session start (project has harness-mem psychographic node) | Call mem_query type=psychographic → apply 5-dimension profile to all subsequent skill dispatch |
Orchestration run active ($HARNESS_DIR/orchestrator/run.json exists with status "running") |
orchestrate |
| Agent tool output received with inter-agent message | orchestrate |
User runs /intervene |
orchestrate |
| 요구사항 정의 필요, 스펙 없음 | spec |
| 빌드/구현 시작, 스펙 승인됨 | go |
| 리뷰/감사/테스트 필요 | audit |
| PR 생성 / CI / 배포 준비 | ship |
Alias Routing
Users can still type legacy command names. Map them:
/spec→ invoke skill spec directly/go→ invoke skill go directly/audit→ invoke skill audit directly/ship→ invoke skill ship directly/discover→ invoke skill discover directly/intervene→ invoke skill orchestrate (intervene mode)/status→ invoke skill orchestrate (status mode)
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 · 196 lines · 26 tokens per session scan A 83bbeb4c09b0
_dispatch is a skill published in the GitHub repository epicsagas/epic-harness (17 stars, last pushed 3d ago), licensed Apache-2.0. It adds 26 tokens to every session and 2,792 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
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auto-perf-optimize
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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
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