layerkit-discover-data-layer

layerkit-discover-data-layer is a skill for Claude Code, Codex from hariharapanigrahy/layerkit. It costs 28 tokens per session (923 once invoked), scanned A, original, MIT.

A code-reading workflow that identifies business events and data fields, such as users, carts, and purchases, from a customer’s project. It produces a draft domain specification with references to the source files.

In plain words
What is it for?
Use it to find event names, tracking calls, data models, and field definitions in TypeScript, JavaScript, Java, and similar codebases.
Why use it?
It gives an integration workstream a documented view of the customer’s data model without relying on vendor documentation. It also avoids opening common files that may contain secrets or credentials.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to find event names, tracking calls, data models, and field definitions in TypeScript, JavaScript, Java, and similar codebases.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hariharapanigrahy/layerkit/layerkit-discover-data-layer
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 hariharapanigrahy/layerkit --skill layerkit-discover-data-layer
Clone the repo
git clone --depth 1 https://github.com/hariharapanigrahy/layerkit

Made for: Claude Code, Codex.

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 layerkit-discover-data-layer

README.md
[![agentmods](https://agentmods.dev/badge/skills/hariharapanigrahy/layerkit/layerkit-discover-data-layer/github.svg)](https://agentmods.dev/skills/hariharapanigrahy/layerkit/layerkit-discover-data-layer)
Your own site
<a href="https://agentmods.dev/skills/hariharapanigrahy/layerkit/layerkit-discover-data-layer"><img src="https://agentmods.dev/badge/skills/hariharapanigrahy/layerkit/layerkit-discover-data-layer/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.

agentmods 80×15 button for layerkit-discover-data-layer

Your own site · 80×15
<a href="https://agentmods.dev/skills/hariharapanigrahy/layerkit/layerkit-discover-data-layer"><img src="https://agentmods.dev/badge/skills/hariharapanigrahy/layerkit/layerkit-discover-data-layer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 923 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00028 $0.00923
Opus 5.5 $0.00011 $0.00369
Sonnet 5.5 $0.00006 $0.00185
Haiku 4.5 $0.00003 $0.00092

Measured 1mo ago against content hash 0b6ec424efce, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

layerkit-discover-data-layer scanned grade A with 1 finding 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 1mo 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

4. Prefer in-repo OpenAPI, JSON Schema, or redacted curl for field hints (`source: openapi|curl|code`).
skills/layerkit-discover-data-layer/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

layerkit-discover-data-layer

Analyze the customer data layer (not vendor docs). Output is a domain_spec proposal that seeds Q3–Q4.

Protocol

  1. List candidate files with narrow deterministic tools (rg --files, exact symbol search), then read source yourself. Do not use deterministic heuristics to infer business domains.
  2. Scan TS/JS/Java (and similar) as the AI agent:
    • event / intent type names
    • analytics or vendor emit call sites
    • DTOs / domain models for user, cart, purchase
  3. Deny-paths (never open or paste):
    • .env, .env.*
    • **/*secret*, **/*credential*
    • **/id_rsa*, **/*.pem, **/keystore*, **/*.p12
  4. Prefer in-repo OpenAPI, JSON Schema, or redacted curl for field hints (source: openapi|curl|code).
  5. Draft domain_spec proposal shape:
{
  "schemaVersion": 2,
  "kind": "domain_spec",
  "id": "domain-spec-<customer>-v1",
  "summary": "Customer domain intents/fields from code",
  "authoredBy": "agent",
  "status": "draft",
  "createdAt": "<ISO>",
  "sources": [
    { "title": "<file role>", "url": "file://<repo-relative-path>", "excerpt": "<short>" }
  ],
  "payload": {
    "id": "<customer-or-commerce>",
    "version": "0.1.0",
    "description": "...",
    "intents": [{ "id": "purchase", "description": "..." }],
    "fields": [
      { "path": "user.email", "type": "string", "description": "...", "required": false }
    ]
  },
  "maker": { "type": "agent", "id": "<agent>" }
}
  1. Bootstrap questionnaire Q3 (intents) / Q4 (fields) only when code supports them; residual gaps stay unanswered (source: unanswered).
  2. Persist:
layerkit proposal validate ./domain-spec.json
layerkit memory append --type research --title "domain discovery" --vendor general --body-file ./discovery-note.md
  1. Next: layerkit-research-vendor (per target vendor).

Multi-vendor packages

When the client package already integrates multiple vendors (adapters, mappers, gateways, destinations):

Read the full file on GitHub · 94 lines

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. 1mo ago First seen · 94 lines · 28 tokens per session scan A 0b6ec424efce

Subscribe to this mod's changes

layerkit-discover-data-layer is a skill published in the GitHub repository hariharapanigrahy/layerkit (8 stars, last pushed 2mo ago), licensed MIT. It adds 28 tokens to every session and 923 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.