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/axiomantic/spellbookWrote 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/axiomantic/spellbook/writing-commands-review)<a href="https://agentmods.dev/commands/axiomantic/spellbook/writing-commands-review"><img src="https://agentmods.dev/badge/commands/axiomantic/spellbook/writing-commands-review/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/axiomantic/spellbook/writing-commands-review"><img src="https://agentmods.dev/badge/commands/axiomantic/spellbook/writing-commands-review.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 | $0.00035 | $0.01241 |
| Opus 5 | $0.00017 | $0.00620 |
| Sonnet 5 | $0.00007 | $0.00248 |
| Haiku 4.5 | $0.00003 | $0.00124 |
Grade A, and why
writing-commands-review 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 8d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MISSION
Evaluate a command against the full quality checklist, identify anti-patterns, and run the testing protocol. Produce a scored review report with actionable fixes.
Invariant Principles
- Structure enables scanning: Agents under pressure skim. Sections, tables, and code blocks catch the eye.
- FORBIDDEN closes loopholes: Every command needs explicit negative constraints. Each rationalization needs a counter.
- Reasoning tags force deliberation:
<analysis>before action,<reflection>after. Without these, agents skip to output.
Quality Checklist
Run every item. No shortcuts.
Structure
- YAML frontmatter with
descriptionfield -
# MISSIONsection with clear single-paragraph purpose -
<ROLE>tag with domain expert persona and stakes -
## Invariant Principleswith 3-5 numbered rules - Execution sections with clear steps (numbered, not prose)
-
## Outputsection defining what agent produces -
<FORBIDDEN>section with explicit prohibitions -
<analysis>tag (pre-action reasoning) -
<reflection>tag (post-action verification)
Content Quality
- Steps are imperative ("Run X", "Check Y"), not suggestive ("Consider X", "You might Y")
- Tables used for structured data, not prose paragraphs
- Code blocks for every shell command and code snippet
- Every conditional has both branches specified (if X, do Y; if not X, do Z)
- No undefined failure modes (what happens when things go wrong?)
- Cross-references use correct paths (verify targets exist)
- Dev-only guards specified where applicable
Behavioral
- Agent knows exactly what to do at every step (no ambiguity)
- Invariant principles are testable, not aspirational
- FORBIDDEN section addresses likely shortcuts the agent would take
- Reflection tag asks specific verification questions, not generic "did I do well?"
- Output section has a concrete format (not "display results")
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.
- 8d ago First seen · 128 lines · 35 tokens per session scan A bd6310c55468
writing-commands-review is a command published in the GitHub repository axiomantic/spellbook (10 stars, last pushed yesterday), licensed MIT. It adds 35 tokens to every session and 1,241 once invoked, about $0.0002 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 2026-09-03.
Other commands, from other repositories
subagent-implementation
Orchestrate implement→review subagent loop until task complete. Reads the approved spec, writes a thin brief to .claude/.scratchpad/, dispatches fresh-context subagents, loops until reviewer signs off, commits per green iteration, then updates repo docs.
documentation
Bootstrap and maintain project documentation surfaces. Two modes: bootstrap (discover doc files, index them in CLAUDE.md) and authoring (scan for unindexed docs, match diff against indexed surfaces, walk stale/incomplete/missing items with Yes/Later/Remind/Skip).
watch-ci
Spawn a background Haiku-backed subagent to watch CI for the current branch (or specified target). Provider-agnostic — the subagent inspects project signals to identify the CI system (GitHub Actions, GitLab CI, CircleCI, etc.) and picks the right CLI. Returns immediately; reports back when CI reaches a terminal state.
session-report
Capture what changed this session and why, scoped to the current branch. Read by ship verbs when synthesizing the commit message; deleted after a successful commit.
integrate
Analyze and enhance AI artifacts to leverage Subcog memory effectively.
add-command
Add a new slash command to the current plugin.