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 skills/apurvbazari/claude-plugins/enginenpx skills add ApurvBazari/claude-plugins --skill enginegit clone --depth 1 https://github.com/ApurvBazari/claude-pluginsWhat 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 | $0.00061 | $0.03074 |
| Opus 5 | $0.00030 | $0.01537 |
| Sonnet 5 | $0.00012 | $0.00615 |
| Haiku 4.5 | $0.00006 | $0.00307 |
Grade A, and why
engine 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 yesterday.
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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engine — the data-only review core
Produce a review-findings object (per ../../schemas/review-findings.schema.json) and RETURN it to
the caller. Write no files; ask no questions. Read references/engine-api.md (the declared input/return
surface) + references/pipeline.md + references/finder-registry.md.
Progress tracking (optional — only when handed taskIds)
If the caller passed taskIds in args (the standalone /lens:review path hands
{ scope, intent, analyze, verify }), mark each handed-in stage task in_progress when you enter that
stage and completed when you leave it, via TaskUpdate keyed on the given taskId. If taskIds is
absent (orchestrator/compute-only callers, vicario reuse, any non-standalone invocation), take no
task action — behavior is unchanged and byte-identical to the data-only contract. Never create tasks.
The finder and verifier subagents you dispatch are task-blind — they emit findings only and never touch
the task list.
Step 0: Pre-flight
Pre-flight runs before Step 1, ahead of its empty-scope short-circuit: an empty diff carrying a malformed 1.5.0 input returns the error envelope, not emptyScope:true. Three jobs, then the stages below run.
1. Validate the 1.5.0 keys. Each is checked against the shape declared in references/engine-api.md § lens:engine — inputs, and a violation raises E_INVALID_INPUT:
modelPolicy— its top-level type first (an object, after the defensive string parse), then its four-key shape, its key types, and the accepted role names. The order is load-bearing: the shape, type and role checks are all key-scoped, so a policy that is not an object has no keys for any of them to judge and would pass all three — and be discarded silently, taking thedenygate with it.verifyVotes— an integer inside the range1..5.model/efforton every call-timeinjectedFindersrecord — the declared vocabularies. A file-registered.claude/lens/settings.mdrecord never raises here; its malformedmodel/effortis normalized-or-dropped here in pre-flight (references/pipeline.md§3) rather than at any stage below, because the plan resolved next is frozen from what survives — and because a human's project config is not the caller's to fix mid-call.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 114 lines · 61 tokens per session scan A 25a5b7243102
engine is a skill published in the GitHub repository ApurvBazari/claude-plugins (0 stars, last pushed 25d ago), licensed MIT. It adds 61 tokens to every session and 3,074 once invoked, about $0.0003 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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