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/andr-ca/agentharness/harness-feedbacknpx skills add andr-ca/agentharness --skill harness-feedbackgit clone --depth 1 https://github.com/andr-ca/agentharnessWrote 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/andr-ca/agentharness/harness-feedback)<a href="https://agentmods.dev/skills/andr-ca/agentharness/harness-feedback"><img src="https://agentmods.dev/badge/skills/andr-ca/agentharness/harness-feedback.svg" alt="Measured on agentmods" 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 | $0.00083 | $0.01876 |
| Opus 5 | $0.00042 | $0.00938 |
| Sonnet 5 | $0.00017 | $0.00375 |
| Haiku 4.5 | $0.00008 | $0.00188 |
Grade A, and why
harness-feedback 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 4d 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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Harness Feedback Loop
When friction is discovered during harness usage — a hook that didn't fire, guidance that was contradictory, a mandate violated in practice, or tool output diverging from documentation — capture and escalate it by default. The goal is to ensure harness improvements flow upstream without requiring users to notice and report them manually.
Procedure
1. Address the immediate problem
Work around or fix the specific friction blocking your session — do not defer this step or leave it for later. Examples:
- A hook expected to run but didn't? Inspect
core.hooksPath, check hook file permissions, run it manually if necessary. - Guidance was unclear? Disambiguate it by reading related docs or asking for clarification.
- A mandate was hard to apply? Document what made it hard and propose a better framing.
2. Log it locally
Append a dated entry to docs/operational/harness-feedback.md (create it with a
short header if it doesn't exist). Use this template:
## [ISO 8601 date] – [one-line summary]
**Recurrence key:** `[stable-kebab-case-slug]`
**Harness version:** [commit SHA or tag of the harness in use]
**What happened:** [The friction event and when you noticed it]
**Root cause:** [Why did this happen? What in the harness design or docs caused it?]
**Impact:** [How did it affect your session or workflow?]
**What agentharness should change:** [Concrete recommendation — a new check, clearer guidance, a new tool, a code fix, etc.]
**Corrective action taken:** [What you did to work around or fix it] Logged upstream as #[issue-number] — or "Not filed upstream (opted out via .agentharness-no-upstream-feedback)".
Optional structured fields. Add any of these when you actually have the information — none are mandatory, and a one-off entry with just the fields above is still a complete, valid entry:
**Event class:** [hook-failure | ambiguous-guidance | mandate-violation | tool-output-mismatch | other]
**Observed vs. inferred:** [Directly observed (you saw the failure happen) or Inferred (you're reasoning from symptoms without a direct repro)]
**Evidence reference:** [Link or path to the transcript, log, or command output that shows this — not the raw content, a pointer to it]
**Severity:** [blocking | degraded | cosmetic]
**Workaround:** [What let the session continue despite the friction, if anything]
**Resolution:** [Fixed upstream in #N | Still open | Won't-fix, because ...]
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.
- 4d ago First seen · 158 lines · 83 tokens per session scan A c83f706efd94
harness-feedback is a skill published in the GitHub repository andr-ca/agentharness (1 stars, last pushed yesterday), licensed MIT. It adds 83 tokens to every session and 1,876 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.
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