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 skills add mishahanin/heading-os-marketplace --skill state-checkgit clone --depth 1 https://github.com/mishahanin/heading-os-marketplaceWrote 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/skills/mishahanin/heading-os-marketplace/state-check)<a href="https://agentmods.dev/skills/mishahanin/heading-os-marketplace/state-check"><img src="https://agentmods.dev/badge/skills/mishahanin/heading-os-marketplace/state-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/skills/mishahanin/heading-os-marketplace/state-check"><img src="https://agentmods.dev/badge/skills/mishahanin/heading-os-marketplace/state-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 | $0.00101 | $0.00756 |
| Opus 5.5 | $0.00040 | $0.00302 |
| Sonnet 5.5 | $0.00020 | $0.00151 |
| Haiku 4.5 | $0.00010 | $0.00076 |
Grade A, and why
state-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 2mo 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.
This is a copy
100% identical to state-check — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
State Check
Run a structured Operational State Check for a function or the full company.
Variables
function: sales | product | partnerships | tribe | research | company-wide context: [Brief situational context — what's happening that prompted this check?]
Instructions
Before running, read:
outputs/operations/workspace/31c-operational-state-model.md— Core operational states for each functionreference/state-check-guide.md— State Check format and four questionscontext/current-data.md— Current metrics and active workstreamscontext/pipeline.md— Active pipeline context
Run a structured State Check using the four questions from the State Check Guide:
1. Sea State (2 min) What external conditions have changed since last check? What's the environment doing?
2. Current State (3 min) What operational state is [function] actually in right now? Not what we want — what's true? Evidence: [list observable signals]
3. Heading Check (2 min) Are we on heading? Have we drifted? Assessment: [on heading / slight drift / significant drift]
4. Course Corrections (3 min) If drift detected: what specific, behavioral adjustments restore the state? Course corrections are behaviors, not goals. "Do X daily" not "achieve Y."
Output format:
Function: [name]
Current State: [one sentence assessment]
On Heading: Yes / Slight drift / Significant drift
Sea State Summary: [2-3 sentences]
Course Corrections: [bulleted list, max 3]
Next State Check: [recommended timing]
Total output: 1 page max. The point is clarity, not comprehensiveness.
What ships with it
1 file 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.
- 2mo ago First seen · 92 lines · 101 tokens per session scan A 81aff7473ae2
state-check is a skill published in the GitHub repository mishahanin/heading-os-marketplace (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 101 tokens to every session and 756 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to state-check, differing in 7 lines, and is treated as a copy.
Other skills, from other repositories
domain-modeling
Use when pinning down domain terminology, building a ubiquitous language or project glossary, disambiguating overloaded or vague terms, or maintaining a CONTEXT.md — or when another skill needs to sharpen the domain model. Do NOT use for recording architectural decisions or for writing implementation specs.
code-review
Iterative, human-in-the-loop code review that detects gaps, presents them for selection, and fixes them in cycles. Supports both diff-based PR review and holistic codebase analysis.
address-pr-review
Address reviewer and bot comments on a GitHub pull request — validate each comment, apply fixes where valid, reply with reasoning, and resolve threads.
interview
Deep requirements gathering through probing questions that surface hidden requirements, edge cases, and trade-offs before implementation.
ideate
Facilitate brainstorming as a thinking partner that extracts and expands latent ideas rather than generating them outright.
writing-artifacts
Use when writing or revising a durable written artifact — README, ADR, design doc, PR description, release notes, runbook, error message, user-facing docs. Gives a positive writing system (reader model, sentence positions, document jobs), not a ban-list. Do NOT use for conversational replies to the user (global…