onboard

onboard is a skill for Claude Code from jongwony/epistemic-protocols. It costs 22 tokens per session (6,507 once invoked), scanned A, original, MIT.

An onboarding guide that recommends useful working protocols from recent sessions or teaches them through a short scenario and quiz. It supports quick recommendations and more guided learning.

In plain words
What is it for?
Use it for onboarding, workflow discovery, re-onboarding after changes, or learning a specific working protocol through practice.
Why use it?
It helps new users discover which structured workflows fit their needs before they begin larger tasks.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: reads .claude/ paths; mentions subagents.

Part of the epistemic-cooperative plugin — 13 skills shipped together

Good fit Use it for onboarding, workflow discovery, re-onboarding after changes, or learning a specific working protocol through practice.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jongwony/epistemic-protocols/onboard
Install

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.

Any agent
npx skills add jongwony/epistemic-protocols --skill onboard
Clone the repo
git clone --depth 1 https://github.com/jongwony/epistemic-protocols

Made for: Claude Code.

Or install epistemic-cooperative, the plugin that ships this one along with the rest of its 13 skills.

Wrote 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.

agentmods badge for onboard

README.md
[![agentmods](https://agentmods.dev/badge/skills/jongwony/epistemic-protocols/onboard.svg)](https://agentmods.dev/skills/jongwony/epistemic-protocols/onboard)
Your own site
<a href="https://agentmods.dev/skills/jongwony/epistemic-protocols/onboard"><img src="https://agentmods.dev/badge/skills/jongwony/epistemic-protocols/onboard.svg" alt="Measured on agentmods" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,507 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Data Exfiltration · line 419
    Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.
    Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00022 $0.06507
Opus 5 $0.00011 $0.03254
Sonnet 5 $0.00004 $0.01301
Haiku 4.5 $0.00002 $0.00651

Measured today against content hash 9aac7b11084b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

onboard 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 today.

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.

epistemic-cooperative/skills/onboard/SKILL.md · 432 lines

How it starts

The opening of the file, as written. The whole thing — 432 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Onboard Skill

Start with a quick recommendation based on recent sessions, then optionally continue to guided learning — so users experience value first, learn second.

Invoke directly with /onboard when the user wants onboarding or protocol discovery.

When to Use

Invoke this skill when:

  • A new user wants to discover which epistemic protocols fit their workflow
  • A user wants to experience protocols through guided practice
  • Re-onboarding after new protocols are added or workflow changes

Skip when:

  • User already knows which protocol to use (direct invocation)
  • Quick single-protocol question (answer directly)

Workflow Overview

Quick Proof:    ENTRY → QUICKSCAN → PICK-1 → EVIDENCE → TRIAL → INSIGHT → NEXT
Targeted:       ENTRY → QUICKSCAN → MAP → SCENARIO → TRIAL → QUIZ → GUIDE
Targeted + std: ENTRY → SCENARIO → TRIAL → QUIZ → GUIDE
Phase Owner Tool Purpose
0. Entry Main Gate Path selection: quick/targeted
1. Quick Scan Main Glob, Read User Context Profile extraction
2a. Pick-1 Main Quick path: select 1 recommendation
2b. Evidence Main Quick path: show 1 evidence card
2. Map Main Targeted path: Profile → Protocol matching
3. Scenario Main Gate Targeted path: context-personalized intervention point
4. Trial Main Gate Real protocol execution (quick: mini trial, targeted: full trial)
4→Q. Insight Main Quick path: post-trial insight card
4→Q. Next Main Gate Quick path: simplified navigation
4→5 LOOP Main Gate Targeted path: post-trial navigation
5. Quiz Main Gate Targeted path: Socratic protocol recognition quiz
6. Guide Main Gate Targeted path: summary + next protocol suggestion

Data Sources

Compact mapping for inline use.

Protocol Cluster When to Use Key Patterns
Aitesis /inquire Planning AI is about to answer without enough observable context External fact queries, verifiable grounding (for prior-session recall → use /recollect)
Euporia /elicit Planning Intent articulated but axis-undetermined; decision coordinates implicit in codebase / rules / past sessions Multi-axis intent without single axis-specific protocol fit; substrate-implicit coordinates surface through cycle-emergent dimensions
Heuresis /ideate Planning Object-level candidate field is empty or has prematurely converged — widen it before any selection is made Zero entry questions (seed vs. blank inferred from the utterance), frame-first mode on a blank entry, no elimination or ranking during generation, every candidate tagged origin ∈ {User, AI}
Proplasma /preview Planning Right before a direction commitment when the candidates cannot be judged from descriptions — contrast cheap discard-committed placeholder probes on user-settled axes Principle-delegation at direction gates ("go with the recommended direction"), option-set reconstruction instead of choosing, "I'd have to see it" decision stalls
Hypotyposis /sketch Planning A form has to be made, intent cannot yet be settled from descriptions, and the user would recognize it on sight — sketch under a settled focus, take marks on a specific version, revise the retained version, finish on the recognized one "I'd know it when I see it", a plan stalled at its first draft, a description rewritten repeatedly instead of made
Prothesis /frame Analysis Unsure which analytical perspective to use Exploration ratio 3:1+ (Read+Grep+Glob vs Edit+Write)
Analogia /ground Analysis Checking if abstract advice fits your situation Abstract pattern application without domain validation
Periagoge /induce Analysis Concrete cases accumulating into an unnamed essence — crystallize the emerging abstraction 3+ instances with essence intuition but no located abstraction; /ground misfit where colimit is forced into substitution
Merismos /apportion Execution An autonomous goal is stated but its unit plan is uncompiled — cut it into coarse units at cited seams and close each unit before the run begins — a derived completion condition where one compiles, a recorded acceptance or a recorded reservation where none does An unattended-run directive ("work through", "go through all", "run until done"), a goal that plainly exceeds one execution horizon, or a stop-hook being configured — each only shows an autonomous interval is intended, so the deciding check is whether the goal already carries units whose completion conditions are settled — closed by a determinate predicate, by a recorded acceptance, or by a recorded reservation; a plan that does is out of scope
Epharmoge /contextualize Verification Output is correct but doesn't fit the accumulated conversation context Mismatch against session-built constraints (user-aware context accumulation)
Elenchus /sublate Verification About to externalize a working context whose apparent sufficiency has decayed Dialectical antithesis per claim under test (provenance / counterfactual / cross-source consistency) before pre-execution sync
Horismos /bound Cross-cutting Deciding what to delegate to AI Boundary probe, domain classification, BoundaryMap
Anamnesis /recollect Cross-cutting Resolving vague recall of prior sessions or discussions — one session, or a line of work, topic, or settled concept spread across several Cross-session state recovery via narrative recognition (Recognition over Retrieval); a unit above one session is composed from its deposits at read time
Katalepsis /grasp Cross-cutting Rapid comprehension verification via intent-scented entry points User-intent grasp for a target present in context and quotable, whoever produced it — reviews, plans, papers, docs, or code changes
Hyphegesis /conduct Cross-cutting Conducting the method of a multi-move work prospect before object-level cognition — order, independence, reconciliation, termination, routing Multi-move work with non-trivial conduct (migrations, staged investigations, entangled adversarial/parallel/synthesis); "how should I approach this whole thing?" meta-questions

Read the full file on GitHub · 432 lines

Files

What ships with it

3 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.

Changes

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.

  1. today Changed · +1 lines 9aac7b11084b
  2. yesterday Changed · -1 lines edf83777899a
  3. 2d ago Changed · -7 lines c572bd99de09
  4. 4d ago Changed c12a08c08730
  5. 8d ago First seen · 439 lines · 22 tokens per session scan A 26ed612d39f2

Subscribe to this mod's changes

onboard is a skill published in the GitHub repository jongwony/epistemic-protocols (160 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 6,507 once invoked, about $0.0001 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.

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