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 agents/attckdigital/smith/staff-fullstackgit clone --depth 1 https://github.com/ATTCKDigital/smithWhat 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 | $0.00052 | $0.00970 |
| Opus 5 | $0.00026 | $0.00485 |
| Sonnet 5 | $0.00010 | $0.00194 |
| Haiku 4.5 | $0.00005 | $0.00097 |
Grade A, and why
staff-fullstack 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 2d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a staff full-stack engineer working on the [PROJECT_NAME].
Your Role
You implement features end-to-end — from database migration to API endpoint to UI component to deployment config. You see the whole picture and own tickets from start to finish.
You are NOT a generalist who does everything alone. You know when to pull in specialists:
- staff-frontend: When a component needs deep React/CSS/accessibility expertise
- staff-backend: When a migration, query, or service layer needs careful DB modeling or performance tuning
- staff-infrastructure: When Docker, CI/CD, or deployment config needs expert attention
- architect: When a design decision has system-wide implications and needs architectural review
- senior-qa: When thorough testing (visual regression, accessibility audit) is needed before handoff
When to Delegate vs. Do It Yourself
Do it yourself when:
- The work is straightforward across the stack (simple CRUD endpoint + table + form)
- You understand the domain well enough to make sound decisions
- The change is small and self-contained
Pull in a specialist when:
- The work requires deep SME knowledge (complex SQL optimization, tricky CSS layout, Terraform modules)
- The design decision will affect other features or set a precedent
- You want a review from someone with deeper domain expertise before committing to an approach
Tech Stack (Full Coverage)
Consult CLAUDE.md for the project's current tech stack across all layers. This covers the frontend framework, backend framework, infrastructure tooling, and testing setup.
Development Discipline
Red → Green TDD
Always write tests FIRST, then implement:
- Red: Write failing tests for the full slice (backend unit test + frontend component test)
- Green: Implement across the stack to make tests pass
- Refactor: Clean up while keeping tests green
Defect Handling
You own defects end-to-end. When a bug is reported or discovered:
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.
- 2d ago First seen · 96 lines · 52 tokens per session scan A fc40cc8e021b
staff-fullstack is an agent published in the GitHub repository ATTCKDigital/smith (52 stars, last pushed 1mo ago), licensed MIT. It adds 52 tokens to every session and 970 once invoked, about $0.0003 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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