Skill Creator
Azure/azqr
Create new skills, modify and improve existing skills, and measure skill performance.
This skill should be used when the user asks to "audit plugin encapsulation", "check self-containment semantics", "find contributor-knowledge assumptions", or invokes /encapsulation.
$ npx skills add jongwony/epistemic-protocols --skill encapsulation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jongwony/epistemic-protocols encapsulation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/jongwony/epistemic-protocols.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/encapsulation .claude/skills/encapsulation && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "encapsulation" agent skill from https://github.com/jongwony/epistemic-protocols/tree/main/.claude/skills/encapsulation into .claude/skills/encapsulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "encapsulation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/jongwony/epistemic-protocols/tree/main/.claude/skills/encapsulationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add jongwony/epistemic-protocols --skill encapsulation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jongwony/epistemic-protocols encapsulation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jongwony/epistemic-protocols.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/encapsulation .agents/skills/encapsulation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "encapsulation" agent skill from https://github.com/jongwony/epistemic-protocols/tree/main/.claude/skills/encapsulation into .agents/skills/encapsulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "encapsulation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jongwony/epistemic-protocols --skill encapsulation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jongwony/epistemic-protocols encapsulation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jongwony/epistemic-protocols.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/encapsulation .cursor/skills/encapsulation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "encapsulation" agent skill from https://github.com/jongwony/epistemic-protocols/tree/main/.claude/skills/encapsulation into .cursor/skills/encapsulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "encapsulation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/jongwony/epistemic-protocols.git --path .claude/skills/encapsulation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add jongwony/epistemic-protocols --skill encapsulation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jongwony/epistemic-protocols encapsulation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jongwony/epistemic-protocols.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/encapsulation .gemini/skills/encapsulation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "encapsulation" agent skill from https://github.com/jongwony/epistemic-protocols/tree/main/.claude/skills/encapsulation into .gemini/skills/encapsulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "encapsulation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install jongwony/epistemic-protocols encapsulationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add jongwony/epistemic-protocols --skill encapsulation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jongwony/epistemic-protocols.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/encapsulation .github/skills/encapsulation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "encapsulation" agent skill from https://github.com/jongwony/epistemic-protocols/tree/main/.claude/skills/encapsulation into .github/skills/encapsulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "encapsulation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jongwony/epistemic-protocols --skill encapsulation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jongwony/epistemic-protocols encapsulation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jongwony/epistemic-protocols.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/encapsulation .opencode/skills/encapsulation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "encapsulation" agent skill from https://github.com/jongwony/epistemic-protocols/tree/main/.claude/skills/encapsulation into .opencode/skills/encapsulation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "encapsulation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
encapsulationThis skill should be used when the user asks to "audit plugin encapsulation", "check self-containment semantics", "find contributor-knowledge assumptions", or invokes /encapsulation.
Encapsulation is an agent skill from jongwony/epistemic-protocols. This skill should be used when the user asks to "audit plugin encapsulation", "check self-containment semantics", "find contributor-knowledge assumptions", or invokes /encapsulation. Reviews LLM-facing prose in this project's plugin SKILL.md files and plugin description metadata for Plugin Encapsulation compliance: prose that assumes contributor documentation knowledge or rephrases banned references to bypass deterministic checks. Project-local contributor tooling.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/audit-engine.md`).
It sits in Agent Workflows, covering Skill authoring. The repository describes itself as: Epistemic protocols for Claude Code — structure human-AI interaction quality at every decision point - https://epistemic-protocols.com. The licence is MIT.
Read from SKILL.md and the folder at commit af5aa79. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadGrepGlobFrom allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are json).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Encapsulation loads about 2k tokens when it runs, and up to ~3.6k if it reads all its reference files. Until then it costs about 121 tokens; SKILL.md has 851 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from jongwony/epistemic-protocols at commit af5aa79, republished under its MIT licence (© jongwony). 851 words, ~2,011 tokens.
.claude/skills/encapsulation/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.The project-local instance of the semantic-audit engine (references/audit-engine.md). The shared mechanism — read-only Claude-judge review, the scope shape, severity calibration, self-application stance, and on-demand slash invocation — is defined in that engine document; read it for the parts this skill holds in common with its published siblings. Below is this instance's principle parameter and the one place its output schema extends the engine's base.
This instance audits LLM-facing prose for Plugin Encapsulation: the runtime contract surface (SKILL.md plus plugin description metadata) must be self-contained and intelligible without contributor documentation. Project-local — its principle is coupled to this repo's deterministic encapsulation check and contributor model, and so (unlike white-bear and zero-shot) it is not decouplable into a portable skill. Read-only: it emits structured findings and writes no fixes.
Surface encapsulation drift that the deterministic verify check (artifact-self-containment BANNED patterns) cannot catch — prose that assumes contributor sidecar knowledge in plain language, or rephrases banned references to evade pattern matching. Findings are presented for review; the human author decides which to rewrite, mark as load-bearing, or dismiss.
Manual invocation only (interactive /encapsulation):
The engine's scope shape applies, specialized to the runtime contract surface this principle governs:
In scope (the runtime contract surface where this principle applies):
*/skills/*/SKILL.md — protocol and utility skill prose (full document; the runtime contract surface).claude-plugin/plugin.json description field — plugin description metadata (discovery/routing layer)Out of scope:
docs/, CLAUDE.md, README*.md, */references/*.md — contributor documentation, where contributor-knowledge prose is appropriate by purpose..claude/rules/ and .claude/principles/ — rule prose authored for contributors..claude/skills/*/SKILL.md — project-local contributor tooling, not part of the marketplace runtime contract surface (this skill is itself in this category)..insights/, memory/ — session and context substrates outside this skill's audit surface.The principle. The packaged runtime contract is SKILL.md plus plugin description metadata; the surface must be self-contained, with no external references (axiom identifiers, rule file paths, design-philosophy concepts, mission/vision docs) that require reading contributor documentation. The deterministic verify check covers literal pattern matches; this audit covers semantic encapsulation.
Two signal types — this instance extends the engine's single-failure-kind shape with a failure-kind dimension:
contributor_assumption — a prose passage that assumes contributor documentation knowledge to be intelligible at the runtime contract surface. The reader of the runtime contract is the LLM agent acting on the protocol, plus the user invoking the skill — neither has read .claude/rules/, .claude/principles/, or docs/. Test: "Does this sentence remain intelligible when read with only the SKILL.md itself and standard background knowledge?" If a sentence references a project-internal concept by name without inline definition, and the concept is not defined elsewhere in the same SKILL.md, the sentence is a finding.
bypass_rephrasing — a prose passage that conveys a banned reference's content without using its banned token. The deterministic check passes; the encapsulation invariant fails. Test: "Would the deterministic check have flagged this if the original token had remained?" If yes, it is a bypass-rephrasing finding.
For each candidate finding, prefer the rewrite that carries the meaning into the runtime surface (compile the relevant rule into SKILL.md Rules sections per CLAUDE.md guidance) or replaces it with a self-contained restatement. Treat ambiguous cases as severity: low and surface them for human triage.
Emit a single JSON object as the final assistant message. This is the engine's base schema plus a failure-kind dimension (by_signal in the summary, signal on each finding):
{
"summary": {
"files_audited": 0,
"findings_total": 0,
"by_signal": {"contributor_assumption": 0, "bypass_rephrasing": 0},
"by_severity": {"high": 0, "medium": 0, "low": 0}
},
"findings": [
{
"file": "<repo-relative path>",
"line": 0,
"signal": "contributor_assumption",
"severity": "high",
"excerpt": "<verbatim text from the file — single line or short span>",
"rationale": "<one sentence: which contributor knowledge is assumed, or which banned reference's content is being rephrased>",
"suggested_rewrite": "<a candidate restatement that compiles the meaning into the runtime surface or removes the assumption>"
}
]
}Severity calibration (per the engine):
| Severity | Surface |
|---|---|
high | Rules sections, Phase prose, plugin description — places where contributor assumption materially blocks LLM operation |
medium | Distinctions, Composition notes, scope-boundary descriptions in supporting sections |
low | Borderline cases where the assumption is recoverable from surrounding SKILL.md context or where the bypass interpretation is judgment-dependent |
When zero findings result, emit the JSON object with empty findings array and zero counts. The summary always emits.
This SKILL.md sits in .claude/skills/, which is project-local contributor tooling — out of the marketplace runtime contract surface and therefore not subject to this audit's scope. The principle still applies in spirit: the prose above should be intelligible without contributor sidecar references, and rewrites should preserve that.
| Surface | Mechanism | Failure mode handled |
|---|---|---|
verify artifact-self-containment | Deterministic literal pattern matching against BANNED tokens | Banned reference tokens leaking into the runtime surface |
encapsulation | Claude-judge semantic review of runtime-surface prose | Contributor-knowledge assumption; BANNED-bypass rephrasing |
white-bear | Sibling semantic audit (published, portable) | Unnecessary competing-target mention drift |
zero-shot | Sibling semantic audit (published, portable) | Few-shot anchoring drift |
The verify check and this audit are complementary on the encapsulation axis: deterministic pattern matching catches token leaks; semantic review catches meaning leaks that survive token absence.
Stage 2 evidence-collection instrument. Findings carry the N=1 dogfooding caveat inherent to a project where the audit definition, the rule prose, and the contributor are entangled. Architectural inscription — promoting any pattern observed across findings into a new BANNED token in the deterministic check — waits on Stage 2 variation-stable retention evidence accumulating across multiple PRs and contributors.
© jongwony, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in .claude/skills/encapsulation of jongwony/epistemic-protocols.
Open the folder on GitHubat commit af5aa79
Encapsulation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Encapsulation this skilljongwony/epistemic-protocols | 173 | — | ~2k | Automated safety check: Pass | MIT | |
| Skill CreatorAzure/azqr | 795 | 89 repos | ~8.2k | Automated safety check: Pass | Apache-2.0 | |
| Claude Code Skill Developer Guidediet103/claude-code-infrastructure-showcase | 10k | 11 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Darwin Skill Optimizeralchaincyf/darwin-skill | 6.2k | 1 repos | ~4.7k | Automated safety check: Pass | MIT | |
| Claude Code Command Developmentanthropics/claude-plugins-official | 38k | 10 repos | ~4.8k | Automated safety check: Pass | Apache-2.0 | |
| Claude Code Plugin Structureanthropics/claude-plugins-official | 38k | 10 repos | ~3.4k | Automated safety check: Pass | Apache-2.0 |
Azure/azqr
Create new skills, modify and improve existing skills, and measure skill performance.
diet103/claude-code-infrastructure-showcase
A guide to creating and managing Claude Code skills with auto-activation: skill-rules.json triggers, hooks, enforcement levels, YAML frontmatter and progressive disclosure.
alchaincyf/darwin-skill
Scores SKILL.md files on a nine-dimension rubric, then improves them in a keep-or-revert loop with independent judge agents, test prompts, git history and human checkpoints.
anthropics/claude-plugins-official
Explains how to write Claude Code slash commands: Markdown files with YAML frontmatter, arguments, file references, bash context and interactive prompts.
anthropics/claude-plugins-official
Explains the directory layout, plugin.json manifest and component organization of a Claude Code plugin, including auto-discovery and portable paths.
rohitg00/ai-engineering-from-scratch
Evaluates an Agent Skill bundle before release for structure, trigger quality, artifact improvement, script correctness, safety, installed-tree integrity and host portability.
jongwony/epistemic-protocols
This skill should be used when the user asks to "run the outcome eval", "paired bare vs protocol", "which decisions did the protocol surface", "count what the AI asked or presented", "does /inquire…
jongwony/epistemic-protocols
This skill should be used when the user asks to "run the eval", "test whether the protocol actually works at runtime", "check type realization", "measure protocol fulfillment", "run the…
jongwony/epistemic-protocols
This skill should be used when the user asks to "verify protocols", "check consistency before commit", "validate definitions", "run pre-commit checks", "verify soundness", or wants to ensure…
jongwony/epistemic-protocols
This skill should be used when the user asks to "formal review", "formal lens review", or invokes /formal-review.
jongwony/epistemic-protocols
The user vaguely recalls something discussed before but cannot name it — one session, or a line of work, topic, or settled concept across several: find it in past records to recognize.
jongwony/epistemic-protocols
A skill your agent uses when the user asks to "check white bear", "audit prohibitions", "find negative framing", or invokes /white-bear.
Categories
This skill should be used when the user asks to "audit plugin encapsulation", "check self-containment semantics", "find contributor-knowledge assumptions", or invokes /encapsulation. Encapsulation is an agent skill from jongwony/epistemic-protocols. This skill should be used when the user asks to "audit plugin encapsulation", "check self-containment semantics", "find contributor-knowledge assumptions", or invokes /encapsulation.
Encapsulation fits situations like: asks to audit plugin encapsulation; check self-containment semantics; find contributor-knowledge assumptions; invokes /encapsulation.
Run `npx skills add jongwony/epistemic-protocols --skill encapsulation -a claude-code`. Or copy the skill folder (.claude/skills/encapsulation in jongwony/epistemic-protocols) into .claude/skills/encapsulation in your project. Claude Code loads it when a task matches its description.
Run `npx skills add jongwony/epistemic-protocols --skill encapsulation -a codex`. Or copy the skill folder (.claude/skills/encapsulation in jongwony/epistemic-protocols) into .agents/skills/encapsulation in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jongwony/epistemic-protocols --skill encapsulation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/encapsulation, .gemini/skills/encapsulation, .github/skills/encapsulation and .opencode/skills/encapsulation in your project.
SKILL.md names no scripts, command-line tools or credentials: Encapsulation is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Grep, Glob.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Encapsulation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2k tokens (SKILL.md is roughly 8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.6k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Encapsulation: Skill Creator (Azure/azqr, 795 stars), Claude Code Skill Developer Guide (diet103/claude-code-infrastructure-showcase, 10k stars), Darwin Skill Optimizer (alchaincyf/darwin-skill, 6.2k stars) and Claude Code Command Development (anthropics/claude-plugins-official, 38k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
jongwony (a GitHub user) maintains it in jongwony/epistemic-protocols, which has 173 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on October 8, 2026.
Source: jongwony/epistemic-protocols on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.