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 rbah31/claude-code-workflow --skill capture-lessonsgit clone --depth 1 https://github.com/rbah31/claude-code-workflowWrote 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/rbah31/claude-code-workflow/capture-lessons)<a href="https://agentmods.dev/skills/rbah31/claude-code-workflow/capture-lessons"><img src="https://agentmods.dev/badge/skills/rbah31/claude-code-workflow/capture-lessons/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/rbah31/claude-code-workflow/capture-lessons"><img src="https://agentmods.dev/badge/skills/rbah31/claude-code-workflow/capture-lessons.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 | $0.00100 | $0.02245 |
| Opus 5.5 | $0.00040 | $0.00898 |
| Sonnet 5.5 | $0.00020 | $0.00449 |
| Haiku 4.5 | $0.00010 | $0.00225 |
Grade A, and why
capture-lessons 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 1mo 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 — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ship & Capture Phase
You are running the final phase of the sprint. Your job is to close the loop: ship the code, capture what was learned, and prepare for the next sprint.
Step 1 — Load context
First, determine the current sprint: look at tasks/sprints/ directories and
find the most recent one (highest number). Call it sprint-XX below.
Read all sprint artifacts:
tasks/sprints/sprint-XX/plan.md— what was plannedtasks/sprints/sprint-XX/build-output.md— what was builttasks/sprints/sprint-XX/review-output.md— what was found in reviewtasks/sprints/sprint-XX/fix-output.md— what was fixedtasks/sprints/sprint-XX/redteam-output.md— security findings (if exists, skip if not)tasks/lessons.md— existing lessons
If any artifact is missing (e.g., no red-team output for a normal sprint), note its absence and continue with what's available.
Step 2 — Create the PR
Prepare a pull request description based on the sprint artifacts:
## Sprint XX — [Theme]
### What changed
[Summary of changes from build-output]
### Key decisions
[Technical decisions and their rationale]
### Testing
[Tests added, coverage changes]
### Security
[Security considerations, red team findings if applicable]
### Review notes
[Anything the PR reviewer should know]
If git is configured, create the PR. Otherwise, save the PR description to
tasks/sprints/sprint-XX/pr-description.md for the human to use.
Step 3 — Update lessons learned
Add new entries to tasks/lessons.md based on what happened this sprint.
Each lesson follows this format:
### [Date] — [Author or "Claude"] — Sprint XX
**Context**: [What was happening]
**What went wrong (or right)**: [What happened]
**Lesson**: [The takeaway — a rule to follow going forward]
Look for lessons in:
- Review findings that were critical (why weren't they caught earlier?)
- Fix output (any recurring patterns?)
- Red team findings (any systemic security issues?)
- Build blockers (what slowed us down?)
- Things that went well (what should we keep doing?)
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.
- 1mo ago First seen · 252 lines · 100 tokens per session scan A e12adbfe3ba2
capture-lessons is a skill published in the GitHub repository rbah31/claude-code-workflow (5 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 100 tokens to every session and 2,245 once invoked, about $0.0004 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 2026-08-31.
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