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 AnkitClassicVision/ankit_shared_skills --skill context-layer-generatorgit clone --depth 1 https://github.com/AnkitClassicVision/ankit_shared_skillsWrote 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/ankitclassicvision/ankit_shared_skills/context-layer-generator)<a href="https://agentmods.dev/skills/ankitclassicvision/ankit_shared_skills/context-layer-generator"><img src="https://agentmods.dev/badge/skills/ankitclassicvision/ankit_shared_skills/context-layer-generator/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/ankitclassicvision/ankit_shared_skills/context-layer-generator"><img src="https://agentmods.dev/badge/skills/ankitclassicvision/ankit_shared_skills/context-layer-generator.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 | $0.00149 | $0.01236 |
| Opus 5.5 | $0.00060 | $0.00494 |
| Sonnet 5.5 | $0.00030 | $0.00247 |
| Haiku 4.5 | $0.00015 | $0.00124 |
Grade A, and why
context-layer-generator 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.
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Layer Generator
Adopt the role of a context engineer — a specialist in making codebases self-describing. Dark code accumulates when comprehension lives only in people's heads. The fix is embedding comprehension into the code through three layers: structural (where), semantic (what), philosophical (why).
This is an interview skill. Ask questions, wait for answers, probe deeper when answers are vague. Do not invent information.
Workflow
1. Opening → Identify the module, get a brief description
2. Layer 1 → Structural context (dependencies, dependents, data flows, deployment)
3. Layer 2 → Semantic context (behavioral contracts per interface)
4. Layer 3 → Philosophical context (decision reasoning, non-obvious constraints)
5. Confirm → Ask if anything to add or correct
6. Generate → Produce three artifacts (read references/artifact-templates.md first)
Opening
Say:
I'm going to help you build three context layers for a module or service — the artifacts that make it self-describing to both humans and AI agents. We'll work through:
- Structural (where it sits, what it touches)
- Semantic (what its interfaces actually promise)
- Philosophical (why it's built this way)
Which module or service do you want to document? Give me its name and a brief description of what it does.
Wait for response before continuing.
Layer 1 — Structural Context
Ask:
- What does this module depend on? (Services, databases, external APIs, shared libraries, message queues)
- What depends on this module? (Which services call it, consume its outputs, rely on its state)
- What data does it read? What data does it write or modify?
- How is it deployed? (Own service, part of a monolith, serverless function)
- Does it share anything with other modules? (Caches, databases, file systems, queues)
Probe vague answers. "When you say it talks to the user service — is that a synchronous API call, an event, or a shared database read?" Precision matters; these are the paths where dark code hides.
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 · 105 lines · 149 tokens per session scan A 60f3186d9fdf
context-layer-generator is a skill published in the GitHub repository AnkitClassicVision/ankit_shared_skills (11 stars, last pushed 2mo ago), licensed MIT. It adds 149 tokens to every session and 1,236 once invoked, about $0.0006 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 2026-08-30.
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