Borrowing it
Nothing to install: this file belongs to luanmorenommaciel/agentspec. 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/luanmorenommaciel/agentspec/main/CLAUDE.mdgit clone --depth 1 https://github.com/luanmorenommaciel/agentspecWrote 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/instructions/luanmorenommaciel/agentspec/claude-md)<a href="https://agentmods.dev/instructions/luanmorenommaciel/agentspec/claude-md"><img src="https://agentmods.dev/badge/instructions/luanmorenommaciel/agentspec/claude-md.svg" alt="Measured on agentmods" 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 | $0.03295 | $0.03295 |
| Opus 5 | $0.01648 | $0.01648 |
| Sonnet 5 | $0.00659 | $0.00659 |
| Haiku 4.5 | $0.00330 | $0.00330 |
Grade A, and why
agentspec CLAUDE.md 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 5d 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 — 291 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgentSpec Development
Spec-Driven Development framework for Data Engineering on Claude Code
Project Context
What is AgentSpec? A Claude Code plugin that provides structured AI-assisted development through a 5-phase SDD workflow, specialized for data engineering with 58 agents, 31 commands, 24 KB domains, and 20 skills (16 distributed in the plugin + 4 repo-local).
Component model (canonical: .claude/kb/shared/component-model.md):
| Layer | Responsibility |
|---|---|
| Agents | EXECUTION — identity, tool scope, model tier, escalation; thin shells around capabilities |
| Skills | CAPABILITY — the HOW: methodology, specialized knowledge, resource usage |
| Commands | ENTRYPOINT — argument surface, mode selection, sequencing of existing pieces |
| KBs | SOURCE OF TRUTH — self-contained deep dives other components trust |
New logic goes to the layer that owns it — the component-model skill walks the decision; the SDD workflow components are the reference implementation.
Current Status: v3.5.0 shipped (spec-linter contract gate, spec-judge behavioral gate, component-model skills suite, marketplace install fix). Linear is the project tracker (source of truth).
Repository Structure
agentspec/
├── .claude/ # Claude Code integration
│ ├── agents/ # 58 specialized agents
│ │ ├── architect/ # 8 system-level design agents
│ │ ├── cloud/ # 10 AWS, GCP, cloud services, CI/CD
│ │ ├── platform/ # 6 Microsoft Fabric specialists
│ │ ├── python/ # 6 Python dev, code quality, prompts
│ │ ├── test/ # 3 testing, data quality, contracts
│ │ ├── data-engineering/ # 15 DE implementation specialists
│ │ ├── dev/ # 4 developer tools & productivity
│ │ └── workflow/ # 6 SDD phase agents
│ │
│ ├── commands/ # 31 slash commands
│ │ ├── workflow/ # SDD commands (7)
│ │ ├── data-engineering/ # DE commands (8)
│ │ ├── core/ # Utility commands (5)
│ │ ├── knowledge/ # KB commands (1)
│ │ ├── review/ # Review commands (2)
│ │ └── visual-explainer/ # Visual documentation commands (8)
│ │
│ ├── skills/ # 19 source skills: sdd-* phase skills + sdd-workflow umbrella,
│ │ │ # GitHub trio (github-cr-adr/-issue, github-post-issue),
│ │ │ # authoring (component-model, create-skill*, create-agent*),
│ │ │ # kb-build, visuals (visual-explainer, excalidraw-diagram),
│ │ │ # agent-router, team comms (meeting-analysis*, standup-report*)
│ │ │ # (* = repo-local, excluded from the plugin; see docs/reference)
│ │
│ ├── sdd/ # SDD framework
│ │ ├── architecture/ # WORKFLOW_CONTRACTS.yaml, ARCHITECTURE.md
│ │ ├── templates/ # 5 document templates (DE-aware)
│ │ ├── features/ # Active development
│ │ ├── reports/ # Build reports
│ │ └── archive/ # Shipped features
│ │
│ └── kb/ # Knowledge Base (24 domains)
│ ├── _templates/ # 7 KB domain templates
│ ├── _index.yaml # Domain registry
│ ├── shared/ # Cross-domain anti-patterns and conventions
│ ├── dbt/ # dbt patterns and concepts
│ ├── spark/ # PySpark, Spark SQL
│ ├── sql-patterns/ # SQL best practices
│ ├── airflow/ # DAG patterns
│ ├── streaming/ # Flink, Kafka, CDC
│ ├── data-modeling/ # Star schema, Data Vault, SCD
│ ├── data-quality/ # GE, Soda, observability
│ ├── lakehouse/ # Iceberg, Delta, catalogs
│ ├── cloud-platforms/ # Snowflake, Databricks, BigQuery
│ ├── ai-data-engineering/ # RAG, vector DBs, features
│ ├── modern-stack/ # DuckDB, Polars, SQLMesh
│ ├── aws/ # Lambda, S3, Glue, SAM
│ ├── gcp/ # Cloud Run, Pub/Sub, BigQuery
│ ├── microsoft-fabric/ # Lakehouse, Warehouse, Pipelines
│ ├── lakeflow/ # Databricks Lakeflow (DLT)
│ ├── medallion/ # Bronze/Silver/Gold architecture
│ ├── supabase/ # pgvector, RLS, Edge Functions, Auth
│ ├── prompt-engineering/ # Chain-of-thought, extraction
│ ├── genai/ # Multi-agent systems, guardrails
│ ├── pydantic/ # Validation, LLM output schemas
│ ├── python/ # Python patterns and idioms
│ ├── testing/ # pytest, fixtures, CI testing
│ └── terraform/ # IaC modules, state, workspaces
│
├── docs/ # Documentation
│ ├── getting-started/ # Installation and first pipeline
│ ├── concepts/ # SDD pillars through DE lens
│ ├── tutorials/ # dbt, star schema, Spark, streaming tutorials
│ └── reference/ # Full catalog: agents, commands, KB domains
│
├── plugin/ # Generated plugin (built by build-plugin.sh)
│ ├── .claude-plugin/ # Plugin manifest + marketplace config
│ ├── agents/ # Copied + path-rewritten agents
│ ├── commands/ # Copied + path-rewritten commands
│ ├── skills/ # 16 skills (15 from .claude/ + 1 plugin-only; repo-local excluded)
│ ├── kb/ # Copied KB domains
│ ├── sdd/ # Templates + architecture (no features/reports/archive)
│ ├── hooks/ # SessionStart workspace init
│ └── scripts/ # init-workspace.sh
│
├── plugin-extras/ # Plugin-only content (merged into plugin/ by build)
│ ├── skills/ # data-engineering-guide
│ ├── hooks/ # hooks.json
│ └── scripts/ # init-workspace.sh
│
├── Makefile # Developer entry point — `make help` lists all targets
├── build-plugin.sh # Builds plugin/ from .claude/ (invokes scripts/generate-agent-router.py)
├── scripts/ # Build tooling (not shipped in plugin)
│ ├── generate-agent-router.py # Regenerates agent-router SKILL.md + routing.json from agent frontmatter
│ └── judge.py # Judge V0: OpenRouter second opinion (backend for /judge command)
├── tests/ # pytest suite (27 tests) — `make test`
├── .shellcheckrc # Lint config for shell scripts
├── CHANGELOG.md # Version history
├── CONTRIBUTING.md # Contribution guide
├── SECURITY.md # Security policy
└── README.md # Project overview
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.
- 5d ago First seen · 291 lines · 3,295 tokens per session scan A 14e9f57988f4
agentspec CLAUDE.md is an instructions file published in the GitHub repository luanmorenommaciel/agentspec (245 stars, last pushed 3d ago), licensed MIT. It adds 3,295 tokens to every session, about $0.0165 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 2026-09-01.
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