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 skills add IgorGanapolsky/ThumbGate --skill capture-feedbackgit clone --depth 1 https://github.com/IgorGanapolsky/ThumbGateWrote 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/igorganapolsky/thumbgate/capture-feedback)<a href="https://agentmods.dev/skills/igorganapolsky/thumbgate/capture-feedback"><img src="https://agentmods.dev/badge/skills/igorganapolsky/thumbgate/capture-feedback/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/igorganapolsky/thumbgate/capture-feedback"><img src="https://agentmods.dev/badge/skills/igorganapolsky/thumbgate/capture-feedback.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00029 | $0.00438 |
| Opus 5 | $0.00015 | $0.00219 |
| Sonnet 5 | $0.00006 | $0.00088 |
| Haiku 4.5 | $0.00003 | $0.00044 |
Grade A, and why
capture-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 9d 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.
What it actually says
Capture Feedback
Record structured feedback after completing a task or encountering an issue.
When to use
- After completing a coding task (positive or negative outcome)
- When a tool call produces unexpected results
- After a test failure or deployment issue
- When the user explicitly wants to record feedback
How it works
Use the capture_feedback MCP tool with:
- signal —
"thumbs_up"or"thumbs_down" - context — Description of what happened and why when the user already said it clearly
- tags — Array of relevant tags for categorization (e.g.,
["test-failure", "refactor"]) - chatHistory — Up to 8 prior recorded entries plus the failed tool call when the thumbs-down signal is vague and the lesson must be distilled from recent context
- relatedFeedbackId — Use when the user adds clarifying detail later and it should refine the existing feedback event
- rubric_scores — Optional object with structured quality scores
Example
Capture feedback: thumbs_down for the failed database migration.
Context: Migration script dropped the wrong index, causing query timeouts.
Tags: database, migration, production-incident
Vague signal recovery
If the user only says thumbs_down, wrong, correct, or this failed, do not stop there. Call capture_feedback with:
- the signal
- any minimal context the user already gave
chatHistorycontaining up to 8 prior recorded entries from the current correction thread- the failed tool call or command when available
relatedFeedbackIdif the user is clarifying an already-open 60-second follow-up session
That lets ThumbGate propose whatWentWrong, whatToChange, and a candidate rule automatically.
Feedback feeds into the prevention rule promotion pipeline. Repeated failures with the same pattern are automatically promoted into enforceable prevention rules.
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.
- 9d ago First seen · 49 lines · 29 tokens per session scan A 1b4fac9d9df7
capture-feedback is a skill published in the GitHub repository IgorGanapolsky/ThumbGate (26 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 438 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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