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 commands/pierry/harness-kit/rungit clone --depth 1 https://github.com/Pierry/harness-kitWhat 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 | $0.00028 | $0.00292 |
| Opus 5 | $0.00014 | $0.00146 |
| Sonnet 5 | $0.00006 | $0.00058 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
run 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 yesterday.
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.
What it actually says
Run intake. Record intent so the status bar tracks it:
.claude/scripts/pipeline.py intent intake
Dispatch the intake subagent via the Task tool (subagent_type: intake), so the heavy repo
exploration runs in an isolated context and only the distilled intake.md returns. Pass the raw idea
(and any repo path the user named) as the prompt.
The subagent explores the repo + context-library, computes feature_id, attaches it with
pipeline.py set-feature, and writes .claude/runtime/outputs/intake/{feature_id}.md with a structured
frontmatter (squad, repos, customers, metric, unknowns) and an <!-- approved: --> marker.
When the subagent returns, relay its report and surface unknowns:
intake saved at {path}.
feature_id: {feature_id}
unknowns: {n} — {short list or "none"}
next: /product-manager:prd
If unknowns is non-empty, name them so the human can fill any that matter before the PRD gate. Do not
block: the pipeline proceeds with the markers in place.
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.
- yesterday First seen · 30 lines · 28 tokens per session scan A c87ff1097ac6
run is a command published in the GitHub repository Pierry/harness-kit (3 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 292 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 2026-08-31.
Other commands, from other repositories
setup-pm-skills
Onboard a new user — find out what they do, recommend the right bundles & top skills, and set up a project CONTEXT.md so every skill is tailored to them.
statusbar-style
Switch the status-bar style (classic / capsule / hairline).
fest-show
Show festival progression (in-progress tasks, roadmap, and dependency view).
superpowers-execute
Execute the current GSD phase plan with Superpowers instead of gsd-execute-phase.
config
Command "config" from sdebruyn/fabric-dw-mcp-cli, covering configuration & defaults, http retry budget, sql retry budget, mcp workspace allowlist {#mcp-workspace-allowlist} and mcp server log level.
deps-age
Analyze dependency freshness and maintenance activity.