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 Mfrostbutter/skill-forge --skill workflow-capturegit clone --depth 1 https://github.com/Mfrostbutter/skill-forgeWrote 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/mfrostbutter/skill-forge/workflow-capture)<a href="https://agentmods.dev/skills/mfrostbutter/skill-forge/workflow-capture"><img src="https://agentmods.dev/badge/skills/mfrostbutter/skill-forge/workflow-capture/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/mfrostbutter/skill-forge/workflow-capture"><img src="https://agentmods.dev/badge/skills/mfrostbutter/skill-forge/workflow-capture.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 | $0.00112 | $0.00616 |
| Opus 5.5 | $0.00045 | $0.00246 |
| Sonnet 5.5 | $0.00022 | $0.00123 |
| Haiku 4.5 | $0.00011 | $0.00062 |
Grade A, and why
workflow-capture 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow Capture
Maintain an append-only journal that survives compaction and /clear, capturing the signal (decisions, sequencing, corrections, dead ends) that should become a skill. Do not log keystrokes; the transcript already does that at the wrong altitude. Capture why, not just what.
At session start
- Determine the active workflow slug (kebab-case, e.g.
figma-site-redesign). - Look for
_worklogs/YYYY-MM-DD-<slug>/WORKLOG.md.- If it exists, read it fully before doing anything. It is your memory.
- If not, create the directory and a new WORKLOG.md with a one-line header naming the workflow and date.
Tag schema
Every entry carries exactly one tag:
- DECISION: what was done and why -> a procedure step
- SEQUENCE: X must precede Y -> ordered steps or preconditions
- CORRECTION: user overrode you -> a hard rule
- DEADEND: tried X, failed because Y -> a "do not do this" warning
- CONVENTION: naming, structure, params, defaults -> reference material
- DISCOVERY: tool quirk, API limit, gotcha -> environment notes
- CHECKPOINT: state snapshot before clear or compaction -> resume anchor
Entry format
Append, never rewrite history.
## [YYYY-MM-DD HH:MM] TAG
One-line summary.
Optional result and fix or lesson.
Tags: comma, separated, keywords
When to append
Append an entry the moment one of these happens:
- The user corrects or overrides something (CORRECTION).
- An approach fails and you switch (DEADEND).
- A non-obvious ordering constraint appears (SEQUENCE).
- You set a reusable convention (CONVENTION).
- A tool behaves unexpectedly (DISCOVERY).
Keep entries short. The lesson matters, not the prose.
Checkpoint and resume
Before any compaction or /clear, write a CHECKPOINT entry: current state, open threads, next intended action. On resume in a fresh window, read the worklog and continue from the last CHECKPOINT plus accumulated tags.
Why this matters
The context window is volatile and mostly noise. A durable tagged journal is the only thing that lets a workflow survive a context reset and later become a skill that makes the next run cheaper and more correct.
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 · 58 lines · 112 tokens per session scan A 9c5b5ad354a4
workflow-capture is a skill published in the GitHub repository Mfrostbutter/skill-forge (4 stars, last pushed 2mo ago), licensed MIT. It adds 112 tokens to every session and 616 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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