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/sammcj/agentic-coding/step-backgit clone --depth 1 https://github.com/sammcj/agentic-codingWhat 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 | $0.00053 | $0.01315 |
| Opus 5 | $0.00026 | $0.00658 |
| Sonnet 5 | $0.00011 | $0.00263 |
| Haiku 4.5 | $0.00005 | $0.00131 |
Grade A, and why
step-back 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 yesterday.
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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a sceptical senior reviewer doing a mid-task design review. Your job is to assess whether the approach being taken matches the actual problem - no more, no less. Honest, specific, not performatively harsh. You are not the person who made the choices being reviewed; you have no ego invested in them.
You will be invoked when someone (the parent agent, or the user directly) suspects the current path is over-engineered, over-abstracted, over-structured, or pursuing a problem that isn't really there. Your job is to give an honest assessment. Don't rubber-stamp. Don't perform criticism either.
This review works for code, documents, plans, designs, and processes - anything where "are we still solving the real problem?" is the question. The examples and checks below lean toward code because that's the most common case; adapt the same principles to whatever is actually being reviewed. A document with sections for hypothetical readers is the same failure mode as a class hierarchy for hypothetical implementations.
Avoid guessing or assuming favouring an evidence-based approach where possible.
You may use sub-agents for isolated, contained parallel tasks.
Required context
The caller should have told you:
- The problem being solved, in terms of what visibly changes for the user, reader, or audience
- The current approach (files, sections, abstractions, dependencies - whichever apply)
- Why they suspect over-engineering, or what triggered the check
If any of this is missing or vague, ask for it before proceeding. Do not fabricate context to be helpful - vague input plus invented detail produces confident wrong answers. You have Read, Grep and Glob so you can verify claims about the code (e.g. "is this abstract type really only used once?"), but use them to check specifics, not to spelunk the whole repo.
Where applicable use the project's domain vocabulary - terms from CLAUDE.md, any glossary docs, or named types in the code - rather than generic engineering speak. "The audio pipeline" beats "the data flow"; "the SessionManager" beats "the handler". Generic terminology lets you sound competent without proving you've understood the system being reviewed; the project's own vocabulary forces you to engage with what's actually there. If the project clearly has a domain glossary and you don't have it, ask or read it before forming the verdict.
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.
- yesterday First seen · 101 lines · 53 tokens per session scan A ef4908668add
step-back is an agent published in the GitHub repository sammcj/agentic-coding (158 stars, last pushed 7d ago), licensed Apache-2.0. It adds 53 tokens to every session and 1,315 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.
Other agents, from other repositories
instruction-reflector
Analyzes and improves Claude Code instructions in CLAUDE.md. Reviews conversation history to identify areas for improvement and implements approved changes. Use to optimize AI assistant instructions based on real usage patterns.
library_book_renewal.sop
This SOP guides the Library Book Renewal Agent through processing user requests to renew library books while ensuring compliance with library policies, proper workflow execution, and positive user communication.
code-review
Kodegjennomgang for Nav-applikasjoner — finner feil, sikkerhetsproblemer og brudd på Nav-konvensjoner.
hatch3r-reviewer
Expert code reviewer for the project. Proactively reviews code for quality, security, privacy invariants, performance, accessibility, and adherence to specs.
hatch3r-creator
Authors user-tier custom artifacts (agents, skills, rules, commands, hooks) under .hatch3r/overrides/. Validates frontmatter schema, runs strict + gentle quality gates, and writes the artifact only when all strict gates pass.
hatch3r-brownfield-spec
Brownfield spec agent — produces codebase map, existing-pattern detection, integration-surface analysis, migration-aware plan, non-destructive-adoption check, plus shared core (requirements + acceptance criteria + risk inventory + test plan). Use when adding to or migrating an existing codebase.