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/jongwony/epistemic-protocols/misusenpx skills add jongwony/epistemic-protocols --skill misusegit clone --depth 1 https://github.com/jongwony/epistemic-protocolsWrote 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/jongwony/epistemic-protocols/misuse)<a href="https://agentmods.dev/skills/jongwony/epistemic-protocols/misuse"><img src="https://agentmods.dev/badge/skills/jongwony/epistemic-protocols/misuse.svg" alt="Measured on agentmods" 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 | $0.00038 | $0.05660 |
| Opus 5 | $0.00019 | $0.02830 |
| Sonnet 5 | $0.00008 | $0.01132 |
| Haiku 4.5 | $0.00004 | $0.00566 |
Grade A, and why
misuse 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 5d 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 — 319 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Misuse Skill
Retrospective Contract Violation Detector — when the user wants to audit past /ground and /induce invocations for silent contract violations, scan session history against contract integrity criteria and surface candidate violations for user-constituted review. Type: (ContractIntegrityOpaque, AI, AUDIT, SessionHistory) → ViolationReview.
Invoke directly with /misuse when the user wants a retrospective audit of past protocol invocations against their declared Phase 0 contracts.
Definition
Misuse (ἔλεγχος, élenchos: examination by drawing out, Socratic refutation): A dialogical act of resolving the opacity of past protocol contract integrity into a recognized violation history, where AI scans session JSONL for /ground and /induce invocations, classifies each against the contract criteria in references/violation-taxonomy.md (LEGITIMATE / VIOLATION / AMBIGUOUS), and the user constitutes the verdict via per-invocation recognition — never AI-resolved verdict assertion.
This skill stands in time-axis dual relationship to /probe. Probe is prospective: when a deficit is unrecognized at the present moment, surface candidate hypotheses with reverse-evidence so the user routes forward. Misuse is retrospective: when contract integrity in past invocations is opaque, surface candidate violations with operational evidence so the user audits backward. Both refuse AI-side resolution; both treat user recognition as the constitutive act.
Phase 4 recognition is structurally homologous to Anamnesis Phase 2 — past-identity synthesis (verifying whether a past act conformed to its contract), not future-trajectory selection. The Differential Future Requirement does not apply: a 1-correct option structure (was-violation / was-legitimate) is legitimate by purpose, not a degradation.
When to Use
Invoke this skill when:
- The user suspects past
/groundor/induceinvocations may have violated contract integrity - The user wants to audit a recent session or set of sessions for silent Sₐ confabulation or stereotype misconflation
- The user wants empirical evidence about misuse patterns to inform calibration of future live nudges or contract refinement
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.
- 5d ago First seen · 319 lines · 38 tokens per session scan A 8a7c52406b22
misuse is a skill published in the GitHub repository jongwony/epistemic-protocols (160 stars, last pushed yesterday), licensed MIT. It adds 38 tokens to every session and 5,660 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 2026-08-30.
Other skills, from other repositories
taiyi-ui-design
TaiyiForge 第 4 阶段 — UI/UX 契约，产出 UI-DESIGN.md。四端通用。.
taiyi-evolve
TaiyiForge 辅助 — 实现后架构与文档同步（architecture-sync）。OpenCode / Claude / Codex / Cursor 通用。.
flow-next-resolve-pr
Resolve PR review feedback. Fetches unresolved threads, triages, fixes, replies and resolves via GraphQL. Use when asked to address review comments.
flow-next-tracker-sync
Project a flow-next spec to a tracker issue (Linear, GitHub, GitLab, Jira) and reconcile two-way. Use when asked to sync to a tracker. NOT plan-sync.
taiyi-diagram-c4
TaiyiForge 辅助 — 从代码反推 C4 架构文档（Observed/Inferred 分层 · Mermaid 真源）。OpenCode / Claude / Codex / Cursor 通用。.
writing-style
Use for technical communication - GitHub/GitLab tickets, PR/MR descriptions, issue comments, code review comments, commit messages. Direct, brief style with no AI-speak. NOT for README.md, public docs, or blog posts.