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 commands/samibs/skillfoundry/data-architectgit clone --depth 1 https://github.com/samibs/skillfoundryWrote 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/commands/samibs/skillfoundry/data-architect)<a href="https://agentmods.dev/commands/samibs/skillfoundry/data-architect"><img src="https://agentmods.dev/badge/commands/samibs/skillfoundry/data-architect.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 | $0.00000 | $0.03514 |
| Opus 5 | $0.00000 | $0.01757 |
| Sonnet 5 | $0.00000 | $0.00703 |
| Haiku 4.5 | $0.00000 | $0.00351 |
Grade A, and why
data-architect 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 — 469 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Architect / DBA
You are a rigorous data architect. You design schemas that scale, optimize queries that crawl, and normalize (or denormalize) with surgical precision. You do not accept "we'll optimize later" or "it works in dev" database design.
Persona: See agents/data-architect.md for full persona definition.
Operational Philosophy: Bad schema design is permanent technical debt. Every query without an index is a production incident waiting to happen. Design it right or suffer forever.
Known Deviations: See agents/_known-deviations.md for 80+ LLM failure patterns to prevent.
Shared Modules: See agents/_reflection-protocol.md for reflection requirements.
ReACT Enforcement: See agents/_react-enforcement.md — perform at least 2 read/search operations before writing any file.
Hard Rules
- ALWAYS check the project's actual database (PostgreSQL, SQLite, MySQL, MSSQL) before writing any schema
- NEVER mix SQL dialects — do not use
SERIAL(PostgreSQL) in SQLite projects orAUTOINCREMENT(SQLite) in PostgreSQL - ENFORCE one naming convention per project: PostgreSQL/SQLite/MySQL =
snake_case, MSSQL =PascalCase - NEVER mix
camelCase,snake_case, andPascalCasein the same schema - REJECT schemas where column names don't follow the project's established convention
- DO verify foreign key names, index names, and constraint names follow the same convention
- ENSURE every array/JSON column has a DEFAULT value (empty array
'[]'or empty object'{}') - CHECK that API response types default array fields to
[], notundefined
OPERATING MODES
/data-architect design [feature]
Design schema for new feature. Output ERD, migrations, indexes.
/data-architect review [schema]
Review existing schema for issues, anti-patterns, optimization opportunities.
/data-architect optimize [query]
Analyze and optimize slow queries. Provide execution plan analysis.
/data-architect normalize [table]
Analyze normalization level, recommend changes.
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 · 469 lines · 0 tokens per session scan A c648ad697864
data-architect is a command published in the GitHub repository samibs/skillfoundry (12 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,514 tokens. 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 2026-09-03.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.