Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/axiomantic/spellbooknpx agentmods add commands/axiomantic/spellbook/feature-discoverWrote 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/feature-discover)<a href="https://agentmods.dev/commands/axiomantic/spellbook/feature-discover"><img src="https://agentmods.dev/badge/commands/axiomantic/spellbook/feature-discover/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/feature-discover"><img src="https://agentmods.dev/badge/commands/axiomantic/spellbook/feature-discover.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 | $0.00027 | $0.05742 |
| Opus 5.5 | $0.00011 | $0.02297 |
| Sonnet 5.5 | $0.00005 | $0.01148 |
| Haiku 4.5 | $0.00003 | $0.00574 |
Grade A, and why
feature-discover 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 1mo 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 — 651 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Discovery (Phase 1.5)
Before ANY Phase 1.5 work begins, verify:
# VERIFICATION TEMPLATE — not executable; substitute actual session values
Required: needs_research is true
Current: [SESSION_PREFERENCES.need_flags.needs_research]
→ If not needs_research: STOP. This phase does not run.
(needs_research gates BOTH Research (Phase 1) and Discovery (Phase 1.5);
a single inclusive-OR flag — unfamiliar code OR fuzzy requirements.)
Required: Phase 1 research complete
Verify: SESSION_CONTEXT.research_findings populated
Verify: Research Quality Score = 100% (or user-bypassed)
Required: Research was done by subagent (not in main context)
If ANY check fails: STOP. Return to Phase 1.
Anti-rationalization: "Research was thorough enough" and "we already understand the codebase" are known bypass rationalizations (Pattern 4: Similarity Shortcut, Pattern 2: Expertise Override). Run the check. Trust the process.
Invariant Principles
- Research informs questions — Questions derive from research findings; never ask what research already answered
- 100% completeness required — Proceed to design only when all 13 validation functions pass; no exceptions without explicit bypass
- Adaptive response handling — User responses trigger appropriate actions; never force exact answers
- Understanding document is the gate — Devil's advocate reviews the understanding document; approval unlocks design
Adaptive Response Handler (ARH) Pattern
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.
- 1mo ago First seen · 651 lines · 27 tokens per session scan A 06861eef8097
feature-discover is a command published in the GitHub repository axiomantic/spellbook (11 stars, last pushed 4d ago), licensed MIT. It adds 27 tokens to every session and 5,742 once invoked, about $0.0001 per session on Opus 5.5. 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
audit-agents-skills
Audit quality of agents, skills, and commands in a Claude Code project.
audit-quiz-coverage
Find quiz coverage gaps from recent guide/CHANGELOG/CC-releases changes and propose new questions.
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.
commit
Stage, commit, and optionally ship further. Pass an escalation token (push, pr, merge, squash, squash merge) to skip the prompt. With no token, commits then asks how far to ship. Delegates message format to the atomic-git-discipline skill.
create-plugin
Guided end-to-end plugin creation workflow with component design, implementation, and validation.
feature-dev
Guided feature development with codebase understanding and architecture focus.