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 commands/lugassawan/swe-workbench/designgit 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/design)<a href="https://agentmods.dev/commands/lugassawan/swe-workbench/design"><img src="https://agentmods.dev/badge/commands/lugassawan/swe-workbench/design.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 | $0.00011 | $0.00723 |
| Opus 5 | $0.00005 | $0.00362 |
| Sonnet 5 | $0.00002 | $0.00145 |
| Haiku 4.5 | $0.00001 | $0.00072 |
Grade A, and why
design 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 3d 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
The user is asking: $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.)
Interrogation mode. Before producing anything, resolve the mode:
- Explicit signal in the invocation is honored without asking. grill-me =
--grill, "grill me", or "grill-me mode". standard =--standard, "standard", or "quick". Strip the signal from $ARGUMENTS and record the resolved mode. - No explicit signal: ask via
AskUserQuestion— one question, header "Mode", options Standard (recommended, listed first) and Grill me. Standard description: "Lightweight clarify — a restatement and at most one question, then proceed." Grill-me description: "Relentlessly walk the decision tree one question at a time, each with a recommended answer, self-answering from the codebase where possible." Use the user's choice.
Standard mode: proceed with the command's existing lightweight clarify (a restatement and at most one clarifying question) — do not ask the mode question again.
Grill-me mode: activate swe-workbench:workflow-grill and run its interrogation loop to completion (exit on shared understanding or when the user says "proceed"). Then thread the emitted ## Resolved decisions block into the command's normal artifact/delegation step below — the same way a ticket-context summary is prepended — and continue as in standard mode.
Delegate to the swe-workbench:senior-engineer subagent. Its response must contain:
- Problem restatement — confirm the real question and surface implicit constraints (scale, team size, change frequency, latency budget, compliance).
- Options — 2–3 candidate approaches, each with sketch, strengths, weaknesses, and reversibility.
- Recommendation — one option chosen, reasoned against Clean Architecture's dependency rule and DDD boundaries where relevant.
- Risks — what could make this choice wrong, and which signals to watch.
If the question is under-specified, the subagent asks clarifying questions before recommending. Call out YAGNI explicitly when the design is premature.
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.
- 3d ago First seen · 29 lines · 11 tokens per session scan A 3a5f17a8f9bb
design is a command published in the GitHub repository lugassawan/swe-workbench (2 stars, last pushed 3d ago), licensed MIT. It adds 11 tokens to every session and 723 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 2026-08-31.
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