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 agentmods add skills/cwinvestments/memstack/api-integrationnpx skills add cwinvestments/memstack --skill api-integrationgit clone --depth 1 https://github.com/cwinvestments/memstackWhat 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 | $0.00098 | $0.02735 |
| Opus 5 | $0.00049 | $0.01367 |
| Sonnet 5 | $0.00020 | $0.00547 |
| Haiku 4.5 | $0.00010 | $0.00274 |
Grade A, and why
memstack-automation-api-integration 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 yesterday.
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 — 344 lines — stays where its author put it; the contents beside it link to each section on GitHub.
API Integration — Building system connector...
Develops system-to-system connectors with REST/GraphQL patterns, authentication flows, rate limit handling, data mapping, error recovery, and SDK wrapper generation.
Activation
When this skill activates, output:
API Integration — Building system connector...
Then execute the protocol below.
Context Guard
| Context | Status |
|---|---|
| User says "API integration", "connect APIs", "sync data" | ACTIVE |
| User says "data mapping" or "rate limiting" | ACTIVE |
| User needs to build a connector between two systems | ACTIVE |
| User wants a visual n8n workflow | DORMANT — use n8n Workflow Builder |
| User wants to receive webhooks | DORMANT — use Webhook Designer |
Common Mistakes
| Mistake | Why It's Wrong |
|---|---|
| "Ignore rate limits" | Getting blocked by the API wastes hours of debugging. Implement rate limiting from day one. |
| "No retry logic" | APIs have transient failures. Without retry + backoff, your sync silently drops data. |
| "Store tokens in code" | Use environment variables or a secrets manager. Tokens in code end up in git history. |
| "Map fields manually every time" | Build a reusable mapping layer. Manual field-by-field transforms are fragile and hard to update. |
| "No pagination handling" | Most APIs return paginated results. If you only read page 1, you're missing data. |
Protocol
Step 1: Gather Integration Requirements
If the user hasn't provided details, ask:
- Source system — where does the data come from? (API name, docs URL)
- Destination — where does it go? (your DB, another API, file)
- Data — what entities are synced? (users, orders, products, events)
- Direction — one-way, two-way, or event-driven?
- Auth — how does the API authenticate? (API key, OAuth 2.0, JWT, Basic)
- Volume — how much data? How often? (1K records/day vs 1M)
Step 2: Implement Authentication
| Auth Type | Implementation | Token Lifecycle |
|---|---|---|
| API Key | Header: X-API-Key: {key} or query param |
Static — rotate manually |
| Bearer Token | Header: Authorization: Bearer {token} |
Expires — refresh needed |
| OAuth 2.0 | Auth code flow → access + refresh tokens | Auto-refresh on 401 |
| JWT | Sign claims → Authorization: Bearer {jwt} |
Short-lived — re-sign |
| Basic Auth | Header: Authorization: Basic {base64} |
Static |
| HMAC | Sign request body → custom header | Per-request signing |
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.
- yesterday First seen · 344 lines · 98 tokens per session scan A 2cd925a14dd8
memstack-automation-api-integration is a skill published in the GitHub repository cwinvestments/memstack (417 stars, last pushed 5d ago), licensed MIT. It adds 98 tokens to every session and 2,735 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
ship
Ship workflow: detect + merge base branch, run tests, review diff, bump VERSION, update CHANGELOG, commit, push, and create a PR. Use for an explicit /ship invocation or when the user requests the full ship, release, or deploy workflow. For an ordinary commit, push, or pull-request publishing request, use the built-in…
plan-ceo-review
CEO/founder-mode plan review. Rethink the problem, find the 10-star product, challenge premises, expand scope when it creates a better product. Four modes: SCOPE EXPANSION (dream big), SELECTIVE EXPANSION (hold scope + cherry-pick expansions), HOLD SCOPE (maximum rigor), SCOPE REDUCTION (strip to essentials). Use when…
design-review
Designer's eye QA: finds visual inconsistency, spacing issues, hierarchy problems, AI slop patterns, and slow interactions — then fixes them. Iteratively fixes issues in source code, committing each fix atomically and re-verifying with before/after screenshots. For plan-mode design review (before implementation), use…
plan-eng-review
Eng manager-mode plan review. Lock in the execution plan — architecture, data flow, diagrams, edge cases, test coverage, performance. Walks through issues interactively with opinionated recommendations. Use when asked to "review the architecture", "engineering review", or "lock in the plan". Proactively suggest when…
autoplan
Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. Surfaces taste decisions (close approaches, borderline scope, codex disagreements) at a final approval gate. One command, fully reviewed plan out. Use when…
retro
Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware: breaks down per-person contributions with praise and growth areas. Use when asked to "weekly retro", "what did we ship", or "engineering retrospective". Proactively…