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.
git clone --depth 1 https://github.com/lugassawan/swe-workbenchWrote 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/commands/lugassawan/swe-workbench/document)<a href="https://agentmods.dev/commands/lugassawan/swe-workbench/document"><img src="https://agentmods.dev/badge/commands/lugassawan/swe-workbench/document/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/commands/lugassawan/swe-workbench/document"><img src="https://agentmods.dev/badge/commands/lugassawan/swe-workbench/document.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 | $0.00458 |
| Opus 5.5 | $0.00010 | $0.00183 |
| Sonnet 5.5 | $0.00005 | $0.00092 |
| Haiku 4.5 | $0.00002 | $0.00046 |
Grade A, and why
document 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.
What it actually says
Target: $ARGUMENTS
If $ARGUMENTS contains a ticket reference, invoke swe-workbench:ticket-context first and prepend its structured summary to the delegation context below. Skip if $ARGUMENTS is free-text with no recognizable ref. (Trigger patterns are defined in that skill's "When to invoke" section.)
Delegate to the swe-workbench:tech-writer subagent. Its output must include:
- Artifact type — which category (README section, ADR, ARCHITECTURE/OVERVIEW, inline comment).
- Target path — the exact file path the artifact will live at.
- Style notes detected — heading case, voice, list style, em-dash usage, and any other conventions observed in existing top-level docs.
- Draft or diff — the content to be written.
- Citations — commit hash or file:line for every factual claim in committed artifacts; conversation excerpt is acceptable only in drafts.
Absolute rule: never invent behavior. If the diff doesn't show it, don't document it.
Plan output: If you (the orchestrator) author a plan based on the subagent's response and that plan modifies the codebase (fix / make / implement) — whether saved to a plan file or passed to ExitPlanMode — first activate swe-workbench:workflow-development in Mode A and embed the rendered ## Workflow section in the plan per skills/workflow-development/templates/plan-workflow-section.md. Run the skill's project-detection (git branch -a, git log --oneline -20, Makefile grep, PR-template lookup) so the placeholders are substituted from this repo, not left as [[detect:…]]. Skip Mode A if the plan is pure analysis, design recommendation, or any output that does not introduce file edits — the Workflow section's phases (Branch / Verify / Deliver) do not apply.
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 Changed · +2 lines 8ffe7aff1ea5
- 1mo ago First seen · 21 lines · 24 tokens per session scan A b3fdfa871f63
document is a command published in the GitHub repository lugassawan/swe-workbench (3 stars, last pushed 4d ago), licensed MIT. It adds 24 tokens to every session and 458 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 2026-08-31.
Other commands, from other repositories
estimate
Fast Fermi bracket for a question. Produces an order-of-magnitude bound in under 2 minutes.
brand-generate
Generate an on-brand document from a saved Brand Profile.
show
Display a past OCR review session.
setup-engine
Configure the project's game engine and version. Pins the engine in CLAUDE.md, detects knowledge gaps, and populates engine reference docs via WebSearch when the version is beyond the LLM's training data.
review
Fast review of staged changes. Critical findings only — no style nits.
assess
Run an AI literacy assessment — scan the repo for evidence, score three disciplines, produce a timestamped report.