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/vgrss/acumen/feedbacknpx skills add VGrss/Acumen --skill feedbackgit clone --depth 1 https://github.com/VGrss/AcumenWhat 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 | $0.00020 | $0.00582 |
| Opus 5 | $0.00010 | $0.00291 |
| Sonnet 5 | $0.00004 | $0.00116 |
| Haiku 4.5 | $0.00002 | $0.00058 |
Grade A, and why
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 2d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feedback
Collect structured feedback from the user and submit it as a GitHub Issue on the Acumen repository (VGrss/Acumen).
Core behavior
Step 1 — Category
Ask the user to pick one:
- Bug report — Something is broken or behaving unexpectedly
- Skill idea — A new skill or enhancement to an existing one
- General feedback — Anything else (UX, docs, process, direction)
Step 2 — Problem
Ask: "What's the problem?"
Guide the user to describe what happened or what's missing. Be specific — ask follow-up questions if the description is vague. A good problem statement names the trigger ("when I run /diagnose…"), the observed behavior, and the expected behavior.
Step 3 — Impact
Ask: "Who does this affect and how?"
Guide the user to articulate:
- Who is impacted (which persona, role, or workflow)
- How often it happens (every time, sometimes, edge case)
- How severe it is (blocker, friction, cosmetic)
Step 4 — Suggested solution (optional)
Ask: "Do you have a solution in mind? (optional, feel free to skip)"
If the user has an idea, capture it. If not, move on — good feedback describes the problem well, not necessarily the fix.
Step 5 — Review and confirm
Format the feedback as a preview and show it to the user:
## Category
{category}
## Problem
{problem description}
## Impact
{impact description}
## Suggested solution
{solution or "None provided"}
Ask the user to confirm or edit before submitting.
Step 6 — Submit
Use the GitHub CLI to create an Issue with a label matching the category:
gh issue create \
--repo VGrss/Acumen \
--label "{category label}" \
--title "{concise title derived from the problem}" \
--body "{formatted body}"
Use these labels based on category:
- Bug report →
bug - Skill idea →
enhancement - General feedback →
feedback
The body should follow this template:
## Problem
{problem description}
## Impact
{impact description}
## Suggested solution
{solution or "_None provided — feedback only._"}
---
_Submitted via `/feedback`_
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.
- 2d ago First seen · 100 lines · 20 tokens per session scan A 9ddfea1a0fef
feedback is a skill published in the GitHub repository VGrss/Acumen (11 stars, last pushed 27d ago), licensed Apache-2.0. It adds 20 tokens to every session and 582 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.
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