Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/paruff/uFawkesAInpx agentmods add skills/paruff/ufawkesai/learnWrote 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/paruff/ufawkesai/learn)<a href="https://agentmods.dev/skills/paruff/ufawkesai/learn"><img src="https://agentmods.dev/badge/skills/paruff/ufawkesai/learn/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/paruff/ufawkesai/learn"><img src="https://agentmods.dev/badge/skills/paruff/ufawkesai/learn.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 | $0.00054 | $0.07905 |
| Opus 5.5 | $0.00022 | $0.03162 |
| Sonnet 5.5 | $0.00011 | $0.01581 |
| Haiku 4.5 | $0.00005 | $0.00791 |
Grade A, and why
learn 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 23d 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 — 836 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Learn
Load trigger:
"load learn skill"Invoke when: Post-release review,/measurecommand anomaly flag, sprint end, or user feedback received. > DORA: AI Capability 6: User-centric focus + Cultural: Learning from failures > Token cost: Low
Migrated from the former
learnagent. It is a skill, not an execution boundary: same tools, same model, same memory — the stage name describes work, not a separate agent runtime.
Invoke when: Post-release review,
/measurecommand anomaly flag, sprint end, or user feedback received. DORA: AI Capability 6: User-centric focus + Cultural: Learning from failures Token cost: Low Output:retrospective-YYYY-MM-DD.md+ action items for@planner
Purpose
Close the product improvement loop. Translate delivery experience and metric signals
into DORA capability gaps, then into concrete @planner inputs. Keeps the suite
self-improving rather than self-repeating.
Scope boundary: This agent handles product retrospectives — what did we learn
about the product, user needs, and team effectiveness? Platform incident postmortems
(what failed in the IDP infrastructure and why) are handled by fawkes/.agents/agents/learn.md.
If an incident affected both product and platform, run both agents and cross-reference outputs.
Trigger Conditions
| Trigger | Source | Priority |
|---|---|---|
/measure anomaly flag |
dora-regression GitHub issue |
High — run within 48hrs |
| Post-release review | Filed by release agent | Medium — run within 1 week |
| Sprint end | Weekly cadence | Low — run Friday of each week |
| User feedback received | Issue labeled user-feedback or platform-feedback |
Medium |
| Dojo learner stuck | Issue or discussion flagged in Dojo repo | Medium |
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.
- 23d ago Changed · +673 lines bd12a9d4c284
- 24d ago First seen · 163 lines · 54 tokens per session scan A 3f16fe87939a
learn is a skill published in the GitHub repository paruff/uFawkesAI (2 stars, last pushed yesterday), licensed MIT. It adds 54 tokens to every session and 7,905 once invoked, about $0.0002 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 2026-09-28.
Other skills, from other repositories
ops-dora
CocoOps DORA metrics — computes four DORA-adapted delivery metrics from Snowflake task history and git log. Extends the longitudinal delivery thesis through the skill-native CocoOps thesis workflow. Invoked via $ops dora.
sprint-progress-report
Generate a comprehensive sprint progress report from Jira with velocity metrics, burndown analysis, blocker identification, and team workload distribution. Use when preparing sprint reviews, standups, or tracking sprint health mid-cycle.
documentation
Use when the user asks to install or maintain a documentation index, keep CLAUDE.md or AGENTS.md inventories synchronized with files, add document metadata, classify documentation, or apply documentation-only setup to a repository.
pave-catalog
Build a service catalog — schema, starter entries, and governance model. Produces what information to capture per service, how it's maintained, and where it lives. Use when asked to "service catalog", "what services do we have", "catalog our services", "service inventory", or "who owns what".
configure-gh-jira-sync-bot
Configures canonical/gh-jira-sync-bot in a repository by creating or updating .github/.jirasyncconfig.yaml following the platform-engineering-charm-template conventions, then validates it. Use when a repository needs GitHub-to-Jira issue synchronization or its Jira sync config must be created, fixed or audited.
infrastructure-rules
Skill for the rules module — discovery, validation, scope, and private-sidecar symlink sync for the top-level rules/ directory (specifications include soft markdown guidelines and strong yaml/json formal constraints). Use when discovering rules (discoverrules), resolving a rule path (resolveruleroot), validating rule…