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 rules/adobe/spacecat-api-service/api-design-implementationgit clone --depth 1 https://github.com/adobe/spacecat-api-serviceWhat 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 | $0.00869 | $0.00869 |
| Opus 5 | $0.00434 | $0.00434 |
| Sonnet 5 | $0.00174 | $0.00174 |
| Haiku 4.5 | $0.00087 | $0.00087 |
Grade A, and why
api-design-implementation 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
API Design and Data Modeling Principles
Core Principles
- API design and implementation starts with understanding both the business use cases and the non-functional requirements, and not directly with implementation.
- Data access patterns should be derived from the business use cases.
- The data models, storage implementation and API endpoints should be informed by and implemented starting from the required data access patterns and the non-functional requirements relevant to the use case.
- Implementation should be done incrementally.
When Planning or Implementing New API Endpoints
1. Clarification Phase - Ask These Questions First
Before planning implementation, systematically gather requirements:
Data Access Patterns:
- Where will this data surface? (internal UI, customer-facing UI, internal services, external services, etc.)
- What query patterns are required? (filtering, sorting, pagination)
- Read vs write frequency and volume?
- Will users need to filter or sort by already known, common root-level fields and simple conditions?
- Will users need to filter or sort by deeply nested, complex field values and conditions?
Data Model:
- What kind of data needs to be surfaced for the use case?
- What type of data: simple fields or complex nested structures?
- How large will the data be? (impacts bandwidth)
- Who can read/write different parts of the data? (access control needs)
- How often will different parts be updated? (concurrent update patterns)
- Will all records have this data or only a subset of the data?
- Are some subsets of the data used and retrieved only for some specific use cases?
Scale and Performance:
- Expected record count and growth rate?
- List operation payload size concerns? (especially mobile)
- Can we use projection to exclude heavy fields?
- Is progressive/lazy loading needed?
- Are counts of all/filtered records required to be surfaced together with the paged query results?
Always ask for clarification if:
- Business use cases are not provided, e.g. "Implement a CRUD API for URLs", "Implement a CRUD API for configurations"
- Requirements include "filter/sort by any field", "sort by a single field required by only one of the use cases" (may need different approach)
- Data has vague or only implied requirements, e.g.
- is mostly free-form with no details regarding which fields are used when and where
- all data fields are always needed with every query (consider single entity)
- all data fields are rarely needed (definitely separate)
- Multiple services update same fields concurrently (coordination strategy needed)
- Different access control for different parts of data (separate entities)
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 · 105 lines · 869 tokens per session scan A abfc625a78cc
api-design-implementation is a cursor rule published in the GitHub repository adobe/spacecat-api-service (10 stars, last pushed 3d ago), licensed Apache-2.0. It adds 869 tokens to every session, about $0.0043 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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