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/fact-check-extract)<a href="https://agentmods.dev/commands/axiomantic/spellbook/fact-check-extract"><img src="https://agentmods.dev/badge/commands/axiomantic/spellbook/fact-check-extract/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/fact-check-extract"><img src="https://agentmods.dev/badge/commands/axiomantic/spellbook/fact-check-extract.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 | $0.00016 | $0.01423 |
| Opus 5 | $0.00008 | $0.00711 |
| Sonnet 5 | $0.00003 | $0.00285 |
| Haiku 4.5 | $0.00002 | $0.00142 |
Grade A, and why
fact-check-extract 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 5d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fact-Check: Claim Extraction and Triage (Phases 2-3)
Invariant Principles
- Extract before judging -- collect all claims before assessing truth
- Categorize by verification method -- each claim type maps to a specific agent and evidence strategy
- Implicit claims count -- naming conventions and code structure assert claims as strongly as explicit comments
Phase 2: Claim Extraction
Sources:
| Source | Patterns |
|---|---|
| Comments | //, #, /* */, """, ''', <!-- -->, -- |
| Docstrings | Function/class/module documentation |
| Markdown | README, CHANGELOG, docs/*.md |
| Commits | git log --format=%B for branch commits |
| PR descriptions | Via gh pr view |
| Naming | validateX, safeX, isX, ensureX |
If a source is inaccessible (no git history, no PR): skip and log ⚠ [Source] unavailable -- skipped. If no claims found across all sources: report "No verifiable claims found" and halt.
CoVe Self-Interrogation on Extracted Claims
After extracting claims from all sources and before triage, apply CoVe self-interrogation (per skills/shared-references/cove-protocol.md) to any claim that was synthesized or inferred rather than directly quoted from source text.
Synthesized claims include:
- Claims where the extractor paraphrased or summarized source text
- Implicit claims inferred from naming conventions (from Naming Convention Scan below)
- Claims combining information from multiple sources
For each synthesized claim, run the three-step protocol:
- Generate 2-3 verification questions targeting the extraction accuracy
- Answer each using the source text (re-read if necessary)
- Revise the claim if any answer contradicts the extraction
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.
- 5d ago First seen · 126 lines · 16 tokens per session scan A b2c201be8d8c
fact-check-extract is a command published in the GitHub repository axiomantic/spellbook (10 stars, last pushed yesterday), licensed MIT. It adds 16 tokens to every session and 1,423 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 2026-09-03.
Other commands, from other repositories
review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
dream
Overnight autoresearch + maintainer sweep that surfaces a MORNING REPORT — suggested changes, issues raised with fixes, and kept improvements. Shadow-first; never auto-pushes. Runs on-demand or scheduled for off-hours.
code-quality-plan-creator
LSP-powered architectural code quality analysis - works with any executor (loop or swarm).
mr-description-creator
Generate and apply MR/PR description directly via gh or glab CLI (project).
follow-up
Review and act on pending reminders. Bare invocation shows all reminders as an indexed list; cron-fired invocation (/follow-up due ) surfaces the specific reminder and waits for a response; /follow-up review lists stale project follow-up entries for per-item disposition (extend/close/promote/skip). Transport-aware…
unforgit-curate
Review and improve Unforgit memory quality.