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/audit-mirage-analyze)<a href="https://agentmods.dev/commands/axiomantic/spellbook/audit-mirage-analyze"><img src="https://agentmods.dev/badge/commands/axiomantic/spellbook/audit-mirage-analyze/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/audit-mirage-analyze"><img src="https://agentmods.dev/badge/commands/axiomantic/spellbook/audit-mirage-analyze.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 | $0.00041 | $0.05858 |
| Opus 5 | $0.00020 | $0.02929 |
| Sonnet 5 | $0.00008 | $0.01172 |
| Haiku 4.5 | $0.00004 | $0.00586 |
Grade A, and why
audit-mirage-analyze 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 10d 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 — 542 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Phases 2-3 and 7: Systematic Audit, Green Mirage Patterns, Fix Verification
Invariant Principles
- Every test function gets audited - No skipping tests that "look fine"; line-by-line analysis catches what scanning misses
- Assertions determine test value - A test without meaningful assertions is worse than no test: it creates false confidence and hides production defects
- Score by pattern, not by intuition - Apply every Green Mirage Pattern as the scoring rubric
- A fix is a new suspect - A remediated assertion gets the same adversarial treatment as the assertion it replaced
Phase 2: Systematic Line-by-Line Audit
For EACH test file, work through EVERY test function. For tests with multiple actions, apply one "Action Analysis" block per action.
### Test: `test_function_name` (file.py:line)
**Purpose (from name/docstring):** What this test claims to verify
**Setup Analysis:**
- Line X: [what's being set up]
- Line Y: [dependencies/mocks introduced]
- Concern: [any setup that hides real behavior?]
**Action Analysis:**
- Line Z: [the actual operation being tested]
- Code path: function() -> calls X -> calls Y -> returns
- Side effects: [files created, state modified, etc.]
**Assertion Analysis:**
- Line A: `assert condition` - Would catch: [what failures] / Would miss: [what failures]
**Verdict:** SOLID | GREEN MIRAGE | PARTIAL
**Gap (if any):** [Specific scenario that passes test but breaks production]
**Fix (if any):** [Concrete code to add]
Code Path Tracing
Trace the COMPLETE path for each test action:
test_function()
|-> production_function(args)
|-> helper_function()
| |-> external_call() [mocked? real?]
| |-> returns value
|-> processes result
|-> returns final
|-> assertion checks final
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.
- 10d ago First seen · 542 lines · 41 tokens per session scan A c1f69fc7c5c1
audit-mirage-analyze is a command published in the GitHub repository axiomantic/spellbook (10 stars, last pushed today), licensed MIT. It adds 41 tokens to every session and 5,858 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 2026-08-31.
Other commands, from other repositories
sdd-verify
Validate implementation matches specs, design, and tasks.
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.
pr-ready
Run the project's pre-commit review loop to determine whether the current branch is ready to push — lint, tests, parallel pr-review-toolkit agents plus an over-engineering audit, fix-and-re-run until convergence.
qa
QA sign-off command. Verifies a change against acceptance criteria, runs the test suite, probes edge cases, and issues a ship / no-ship verdict via the qa-lead agent.
gentle-sdd-apply
Implement SDD tasks — writes code following specs and design.
gentle-sdd-verify
Validate implementation matches specs, design, and tasks.