Borrowing it
Nothing to install: this file belongs to AsiaOstrich/EngramGraph. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AsiaOstrich/EngramGraph/main/.agents/skills/ai-collaboration-standards/SKILL.mdgit clone --depth 1 https://github.com/AsiaOstrich/EngramGraphWrote 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/asiaostrich/engramgraph/ai-collaboration-standards)<a href="https://agentmods.dev/skills/asiaostrich/engramgraph/ai-collaboration-standards"><img src="https://agentmods.dev/badge/skills/asiaostrich/engramgraph/ai-collaboration-standards/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/asiaostrich/engramgraph/ai-collaboration-standards"><img src="https://agentmods.dev/badge/skills/asiaostrich/engramgraph/ai-collaboration-standards.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 | $0.00088 | $0.01761 |
| Opus 5.5 | $0.00035 | $0.00704 |
| Sonnet 5.5 | $0.00018 | $0.00352 |
| Haiku 4.5 | $0.00009 | $0.00176 |
Grade A, and why
ai-collaboration-standards 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 14d 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 — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Collaboration Standards
Language: English | 繁體中文
Version: 1.1.0 Last Updated: 2026-01-25 Applicability: Claude Code Skills
AI Skills Hierarchy | AI 技能層級
This skill is part of a three-layer AI collaboration system:
| Layer | Skill | Question it Answers | 回答的問題 |
|---|---|---|---|
| Behavior (Immediate) | /ai-collaboration (this) |
"How should AI respond accurately?" | 「AI 如何準確回應？」 |
| Configuration (Session) | /ai-instruction-standards |
"What to write in CLAUDE.md?" | 「CLAUDE.md 該寫什麼？」 |
| Architecture (Long-term) | /ai-friendly-architecture |
"How to structure code for AI?" | 「如何讓專案對 AI 友善？」 |
Purpose
This skill ensures AI assistants provide accurate, evidence-based responses without hallucination.
Quick Reference
Unified Tag System
This skill uses two complementary tag categories:
Category 1: Certainty Tags (for analyzing existing content)
| Tag | Use When |
|---|---|
[Confirmed] |
Direct evidence from code/docs |
[Inferred] |
Logical deduction from evidence |
[Assumption] |
Based on common patterns (needs verification) |
[Unknown] |
Information not available |
[Need Confirmation] |
Requires user clarification |
Category 2: Derivation Tags (for generating new content)
| Tag | Use When |
|---|---|
[Source] |
Direct content from spec/requirement |
[Derived] |
Transformed from source content |
[Generated] |
AI-generated structure |
[TODO] |
Requires human implementation |
When to Use Which:
| Workflow | Primary Tags |
|---|---|
| Code analysis | Certainty Tags |
| Reverse engineering | Certainty Tags |
| Forward derivation | Derivation Tags |
| Spec generation | Derivation Tags |
Source Types
| Source Type | Tag | Reliability |
|---|---|---|
| Project Code | [Source: Code] |
⭐⭐⭐⭐⭐ Highest |
| Project Docs | [Source: Docs] |
⭐⭐⭐⭐ High |
| External Docs | [Source: External] |
⭐⭐⭐⭐ High |
| Web Search | [Source: Search] |
⭐⭐⭐ Medium |
| AI Knowledge | [Source: Knowledge] |
⭐⭐ Low |
| User Provided | [Source: User] |
⭐⭐⭐ Medium |
What ships with it
2 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.
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.
- 14d ago First seen · 222 lines · 88 tokens per session scan A 5b37aaa90283
ai-collaboration-standards is a skill published in the GitHub repository AsiaOstrich/EngramGraph (3 stars, last pushed today), licensed MIT. It adds 88 tokens to every session and 1,761 once invoked, about $0.0004 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 2026-10-16.
Other skills, from other repositories
kivgraph
Use Kivgraph's local MCP server to search symbols, read their source, and follow references, dependencies, cross-repository consumers and graph status in the indexed code graph.
mushroom
Live graph memory for agents — query and create entities, derive relationships by rule, explain why two things are associated, read the graph at a past commit, ask what a change would do, and answer as one role. Trigger on: memory, remember, recall, relationship, entity, association, why are X and Y related, as of…
omnigraph
Operate OmniGraph graphs and deployments. Use for .pg schemas, .gq queries, OmniGraph CLI commands, file:///s3:///az:// graph URIs, cluster.yaml, operator config, bearer-authenticated servers, graph-backed knowledge or memory, Blob values, embeddings, branches, commits, and change feeds. Apply especially before schema…
code-graph
This skill should be used when understanding code structure, finding dependencies between functions/classes, tracing call graphs, or exploring code relationships. Trigger phrases include 'code graph', 'call graph', 'who calls', 'what calls', 'find dependencies', 'code structure', 'inheritance', 'find paths'.
usage
Query LeanKG knowledge graph for code understanding. Use when exploring a codebase, finding functions, tracing dependencies, or calculating impact radius.
codestory-grounding
Use when discovering repository structure, tracing relationships, analyzing change impact, or validating CodeStory retrieval or an installed plugin through the CodeStory plugin MCP. Skip only for bounded inspection or editing of named files that does not require those operations.