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 agentmods add skills/dioptx/weft/wf-analyzenpx skills add dioptx/weft --skill wf-analyzegit clone --depth 1 https://github.com/dioptx/weftWrote 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/dioptx/weft/wf-analyze)<a href="https://agentmods.dev/skills/dioptx/weft/wf-analyze"><img src="https://agentmods.dev/badge/skills/dioptx/weft/wf-analyze.svg" alt="Measured on agentmods" 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 | $0.00024 | $0.00241 |
| Opus 5 | $0.00012 | $0.00120 |
| Sonnet 5 | $0.00005 | $0.00048 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
wf-analyze 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 4d 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
Analyze Weft Workflow Runs
Read-only. Aggregates the event log into per-template metrics and surfaces recurring friction.
Arguments
$ARGUMENTS
Instructions
-
Run:
python3 "${CLAUDE_PLUGIN_ROOT}/core/cli.py" analyze $ARGUMENTS -
With no arguments, it reports across all templates. Pass
--template NAMEto scope to one. -
Present results in a readable format, not raw JSON.
What it outputs
- Per-template step durations (median and p90)
- Loop counts and guard-block counts per step
- Abandonment and stall counts
- Slowest step per template
- A recurring-friction section, joined from
workflow-qa.jsonl
Examples
/wf-analyze— metrics across all templates/wf-analyze --template feature-workflow— scope to one template
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.
- 4d ago First seen · 36 lines · 24 tokens per session scan A 4822e23862b8
wf-analyze is a skill published in the GitHub repository dioptx/weft (23 stars, last pushed 19d ago), licensed MIT. It adds 24 tokens to every session and 241 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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