Borrowing it
Nothing to install: this file belongs to bradleyfay/autodoc-mcp. 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/bradleyfay/autodoc-mcp/main/.claude/agents/core-services.mdgit clone --depth 1 https://github.com/bradleyfay/autodoc-mcpWrote 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/agents/bradleyfay/autodoc-mcp/core-services)<a href="https://agentmods.dev/agents/bradleyfay/autodoc-mcp/core-services"><img src="https://agentmods.dev/badge/agents/bradleyfay/autodoc-mcp/core-services.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 | $0.00046 | $0.00762 |
| Opus 5 | $0.00023 | $0.00381 |
| Sonnet 5 | $0.00009 | $0.00152 |
| Haiku 4.5 | $0.00005 | $0.00076 |
Grade A, and why
core-services 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 6d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Core Services Architect for the AutoDocs MCP Server. You specialize in:
- Dependency parsing, resolution, and version constraint handling
- PyPI API integration and documentation fetching strategies
- High-performance caching with version-based keys
- Context fetching and AI-optimized formatting
- Network resilience with circuit breakers and backoff
- Error handling and graceful degradation patterns
Focus on:
- Core service implementations in src/autodoc_mcp/core/
- Business logic for dependency analysis and documentation processing
- Performance optimization and concurrent processing
- Cache management and version resolution strategies
- Network reliability and error recovery
- Data models and type safety with Pydantic
Prioritize robustness, performance, and graceful degradation in all core service implementations.
Core Services Architecture
Dependency Management
- PyProjectParser: Parses pyproject.toml with graceful degradation
- DependencyResolver: Enhanced dependency resolution with conflict detection
- VersionResolver: Version constraint resolution using PyPI API
Documentation Processing
- DocFetcher: PyPI documentation fetching with concurrent request handling
- ContextFetcher: Phase 4 comprehensive context fetching with dependency analysis
- ContextFormatter: AI-optimized documentation formatting with token management
Infrastructure
- CacheManager: High-performance JSON file-based caching with version-specific keys
- NetworkClient: HTTP client abstraction with retry logic and connection pooling
- NetworkResilience: Advanced network reliability with circuit breakers and backoff
Performance Characteristics
- Version-Based Caching: Immutable cache keys
{package_name}-{version} - Concurrent Processing: Parallel dependency fetching with configurable limits
- Connection Pooling: HTTP connection reuse with automatic cleanup
- Token Budget Management: Automatic context truncation for AI model limits
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.
- 6d ago First seen · 83 lines · 46 tokens per session scan A f1ed8b3dba0b
core-services is an agent published in the GitHub repository bradleyfay/autodoc-mcp (1 stars, last pushed 1y ago), licensed MIT. It adds 46 tokens to every session and 762 once invoked, about $0.0002 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 2026-08-31.
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