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 rules/espenandreass1/agentslice/ai-coding-workflowgit clone --depth 1 https://github.com/Espenandreass1/agentsliceWhat 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 | $0.00411 | $0.00411 |
| Opus 5 | $0.00205 | $0.00205 |
| Sonnet 5 | $0.00082 | $0.00082 |
| Haiku 4.5 | $0.00041 | $0.00041 |
Grade A, and why
ai-coding-workflow 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.
What it actually says
AgentSlice Rules
Follow AGENT_RULES.md; docs/planning/workflow-state.md alone controls active phase and approval fields.
At every start, resume, or phase change, read AGENT_RULES.md, docs/planning/active-context.md, docs/planning/workflow-state.md, docs/planning/current-slice.md, and docs/planning/checkpoint.md. The checkpoint is a handoff summary, never state truth. Then add only role context: planning reads vision, tech stack, live next slices; build reads approved spec and coding rules; QA reads approved spec, changed files, QA plan, plus one relevant prior QA report only when needed; release reads current spec, QA report, and changelog.
Do not bulk-read historical folders. Use docs/archive/README.md plus targeted search only for a concrete historical need.
Keep the four gates unchanged: human slice approval, human spec approval, independent QA PASS/PASS WITH NOTES, then human release approval. Never implement without the first two, recommend release after FAIL, or deploy without the last. Quick fixes remain fully gated and never reduce auth, ownership, data, privacy, commerce, shared-contract, database/RLS, migration, or production safeguards.
Keep active documents compact: active-context.md ≤180 lines; checkpoint.md ≤80 lines; next-slices.md has one to three living candidates; decisions.md has active constraints only; changelog entries are short and user-facing. At handoff refresh the checkpoint; after a human-approved gate archive only superseded history indexed by docs/archive/README.md. QA defaults to focused acceptance/domain regression and must state any full-suite trigger. Do not parallelize by default; independent QA/review is the normal exception. Keep output compact and link to earlier evidence instead of repeating it.
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 · 18 lines · 411 tokens per session scan A 91e52994cbf5
ai-coding-workflow is a cursor rule published in the GitHub repository Espenandreass1/agentslice (4 stars, last pushed 7d ago), licensed MIT. It adds 411 tokens to every session, about $0.0021 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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