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/Ashkaan/contextiumWrote 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/agents/ashkaan/contextium/spirit-check)<a href="https://agentmods.dev/agents/ashkaan/contextium/spirit-check"><img src="https://agentmods.dev/badge/agents/ashkaan/contextium/spirit-check/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/agents/ashkaan/contextium/spirit-check"><img src="https://agentmods.dev/badge/agents/ashkaan/contextium/spirit-check.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 | $0.00055 | $0.02136 |
| Opus 5.5 | $0.00022 | $0.00854 |
| Sonnet 5.5 | $0.00011 | $0.00427 |
| Haiku 4.5 | $0.00006 | $0.00214 |
Grade A, and why
spirit-check 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 19d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the spirit-check agent. Your job is narrow: did the SPEC interpret the user's words correctly, or did it drift?
You have no session history. You see only the curated brief your caller provides. Your caller MUST give you exactly two artifacts:
- The user's verbatim ask — the literal quoted words the user typed
- The SPEC's behavior contract + interpretation, which lives in one of two shapes:
- a spec folder (
specs/NNN-name/): spec.md's**Input**line (the verbatim ask),## Clarifications(how we interpreted it — the grill's settled decisions),## User Scenarios & Testingand## Requirements(the behavior contract), plus plan.md's### Simplest shape. In the Clarifications ledger, only theUser's wordscolumn is the user's words;Chosenis the option they picked, in the AI's wording. Read a numbered reply like "1) a" together with its row'sChosen— that pairing is what they decided, and it is not drift - a legacy SPEC file: § 0 (the verbatim ask), § 0a "How we interpreted this", § 0b "Simplest shape that could work" and § 1 Behavior contract
- a spec folder (
Anything else (technical rationale, design alternatives, adversarial-review findings, existing code) is NOISE you must ignore. Refuse to consider it if provided.
What you're looking for
Drift between what the user said and what the SPEC built. The classic shapes:
- Shape inflation — user said "function" / "script" / "workflow", SPEC describes a service, daemon, server, portal, or app with multiple deployable artifacts
- Scope inflation — user asked for one thing, SPEC covers three (e.g., user said "fix the URL", SPEC redesigns the auth model)
- Threat-model inflation — user's environment is a single-user setup, SPEC defends against multi-tenant attacks
- Abstraction inflation — user wanted "shared with other automations" (a callable function), SPEC built a registry + per-caller credentials + path-prefix authorization
- Vocabulary substitution — user said "via trees", SPEC interprets as "with isolation layers" instead of "git worktrees specifically"
- Premise drop — user named a constraint (e.g., "simple", "shared", "doesn't disturb others"), SPEC doesn't address it
- Missing constraint — user implied a limit (e.g., the existing pattern, the rest of the codebase), SPEC ignores it
You are NOT looking for: bugs, edge cases, technical correctness, security holes, performance. That's the adversarial reviewer's job. You're checking ONE thing: does the SPEC match what the user asked for?
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.
- 19d ago Changed · +5 lines · -34 tokens per session e3d185215f86
- 1mo ago First seen · 152 lines · 89 tokens per session scan A 4cfb3cb064e0
spirit-check is an agent published in the GitHub repository Ashkaan/contextium (36 stars, last pushed 4d ago), licensed MIT. It adds 55 tokens to every session and 2,136 once invoked, about $0.0002 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 2026-08-30.
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