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 Liberty91LTD/cti-skills --skill feedback-loopsgit clone --depth 1 https://github.com/Liberty91LTD/cti-skillsWrote 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/liberty91ltd/cti-skills/feedback-loops)<a href="https://agentmods.dev/skills/liberty91ltd/cti-skills/feedback-loops"><img src="https://agentmods.dev/badge/skills/liberty91ltd/cti-skills/feedback-loops/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/liberty91ltd/cti-skills/feedback-loops"><img src="https://agentmods.dev/badge/skills/liberty91ltd/cti-skills/feedback-loops.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00024 | $0.00713 |
| Opus 5.5 | $0.00010 | $0.00285 |
| Sonnet 5.5 | $0.00005 | $0.00143 |
| Haiku 4.5 | $0.00002 | $0.00071 |
Grade A, and why
feedback-loops 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 2mo 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feedback Loops
Feedback is Phase 6 of the CTI Hyperloop. Without it, the cycle is open-ended and quality degrades over time.
Types of Feedback
1. Consumer Feedback
Intelligence consumers (stakeholders) assess the value of products they receive.
Collection points:
- After every significant product delivery
- During quarterly PIR reviews
- During stakeholder briefings
Questions:
| Question | Response Options |
|---|---|
| Was this intelligence useful for your decision-making? | Very useful / Somewhat useful / Not useful |
| Was it delivered in time to act on? | Yes / Partially / No |
| Was the format appropriate for your needs? | Yes / Too technical / Too high-level / Wrong format |
| Was the confidence assessment helpful? | Yes / Unclear / Not included |
| What should we prioritise next? | Free text |
Actions:
- Useful + timely → Continue current approach, reinforce collection sources
- Useful + late → Improve detection/triage speed, adjust collection frequency
- Not useful → Review PIR alignment, stakeholder needs, product format
- Format wrong → Adjust per stakeholder-management skill
2. Source Quality Tracking
Track the reliability of intelligence sources over time.
For each source used in products:
- Was the information confirmed, partly confirmed, or disproven?
- Did the source's Admiralty rating need adjustment?
- Were there timeliness issues?
Actions:
- Consistently confirmed → Upgrade reliability rating (e.g., C → B)
- Inconsistent → Maintain or downgrade rating
- Repeatedly disproven → Downgrade to D or E
- Feed updates into source-assessment guidance
3. Analyst Retrospectives
After significant investigations or assessments:
Questions:
- What analytical techniques were applied? Were they effective?
- Were key assumptions validated or invalidated?
- Were there intelligence gaps that could have been filled?
- Were alternative hypotheses adequately considered?
- What would you do differently?
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.
- 2mo ago First seen · 99 lines · 24 tokens per session scan A 16ba39ddcff6
feedback-loops is a skill published in the GitHub repository Liberty91LTD/cti-skills (36 stars, last pushed 4d ago), licensed MIT. It adds 24 tokens to every session and 713 once invoked, about $0.0001 per session on Opus 5.5. 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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