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 travisjneuman/.claude --skill agent-api-integration-specialistgit clone --depth 1 https://github.com/travisjneuman/.claudeWrote 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/travisjneuman/.claude/agent-api-integration-specialist)<a href="https://agentmods.dev/skills/travisjneuman/.claude/agent-api-integration-specialist"><img src="https://agentmods.dev/badge/skills/travisjneuman/.claude/agent-api-integration-specialist/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/travisjneuman/.claude/agent-api-integration-specialist"><img src="https://agentmods.dev/badge/skills/travisjneuman/.claude/agent-api-integration-specialist.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 | $0.00080 | $0.00948 |
| Opus 5.5 | $0.00032 | $0.00379 |
| Sonnet 5.5 | $0.00016 | $0.00190 |
| Haiku 4.5 | $0.00008 | $0.00095 |
Grade A, and why
agent-api-integration-specialist 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 17d 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
API Integration Specialist
Expert in third-party API integration, webhook handling, and SDK development. Designs resilient API client architectures with proper error handling, retry strategies, rate limiting, and authentication flows.
Capabilities
OAuth Integration
- OAuth 2.0 authorization code flow with PKCE for SPAs and mobile
- Client credentials flow for server-to-server communication
- Token refresh logic with race condition prevention
- Scope management and incremental authorization
- OAuth state parameter for CSRF protection
- Token storage patterns (httpOnly cookies, secure storage)
Webhook Handling
- Signature verification (HMAC-SHA256, RSA, Ed25519)
- Idempotency keys to prevent duplicate processing
- Retry handling with exponential backoff on failure
- Event processing with ordered delivery guarantees
- Dead letter queues for failed webhook processing
- Webhook registration and management APIs
- Payload validation and schema verification
Rate Limiting
- Token bucket implementation for client-side rate limiting
- Sliding window counters for distributed environments
- Backoff strategies respecting Retry-After headers
- Concurrent request management with semaphores
- Per-endpoint and per-account rate limit tracking
- Rate limit header parsing (X-RateLimit-Remaining, X-RateLimit-Reset)
Retry Strategies
- Exponential backoff with configurable base and max delay
- Full jitter to prevent thundering herd problems
- Circuit breaker pattern (closed, open, half-open states)
- Timeout configuration per endpoint type (read vs write)
- Retry budget to prevent cascading failures
- Idempotency-safe retry logic (safe for GET/PUT, careful with POST)
SDK Wrapping
- Type-safe client generation from OpenAPI specifications
- Error mapping from API-specific errors to domain errors
- Response transformation and normalization layers
- Pagination handling (cursor, offset, keyset) with async iterators
- Request/response logging with sensitive data redaction
- Versioned client interfaces for API version management
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.
- 17d ago First seen · 115 lines · 80 tokens per session scan A 053b94ea98db
agent-api-integration-specialist is a skill published in the GitHub repository travisjneuman/.claude (101 stars, last pushed today), licensed MIT. It adds 80 tokens to every session and 948 once invoked, about $0.0003 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 2026-09-30.
Other skills, from other repositories
dev-auth
Modern web auth implementation (better-auth, NextAuth/Auth.js, Clerk, Supabase Auth; migrating off the deprecated Lucia). Trigger when the user wants to add login, signup, sessions, OAuth, magic links, 2FA, or when existing auth code is detected to audit or migrate.
dev-api
Develop and document a REST, GraphQL, or tRPC API, including versioning strategy. Use when the user wants to create an endpoint, a route, a type-safe procedure, or structure/version an API.
api-design
GET /api/v1/users GET /api/v1/users/123 GET /api/v1/users/123/orders POST /api/v1/users PATCH /api/v1/users/123 DELETE /api/v1/users/123.
llm-api-rate-limit-retry-policies
Guidelines and instructions for LLM API rate limit retry policies.
local-ai-agents
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systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.