stci-dataops
Skill2 starsChanged 10 months agoMITView on GitHub
Evaluate and onboard LLM pricing sources into STCI with evidence-backed source profiles, schema-valid observations, collector changes, and review receipts. Use when researching a provider or aggregator, assessing a pricing feed, or implementing an STCI collector; trigger with "evaluate this pricing source", "add a provider to STCI", or "review this collector".
The file
We split this skill into the rules it gives an agent
7 rules. About 0 are common, 7 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈7
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 32
Read the current observation schema, collector base class, methodology, source profile template, and legal-risk register before proposing …
- Distinctive: line 34
Use existing dependencies and test fixtures.
- Distinctive: line 58
Stop in profile mode after presenting it.
- Distinctive: line 62
Run the narrow test first, then the repository suite.
- Distinctive: line 69
Proceed: read public documentation.
- Distinctive: line 109
Terms or permissions unclear: stop before automation and request legal or owner review.
- Distinctive: line 111
Authentication required: document the mechanism; never request secrets in chat or place them in code, fixtures, URLs, or logs.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
STCI Data Operations
Overview
Turn a proposed pricing source into a reproducible evidence packet and, when requested, a tested STCI collector change. Treat published prices as time-sensitive evidence and legal conclusions as a human-review boundary; see the source evaluation rubric.
Prerequisites
- Work from the STCI repository root with Python 3.11 or later.
- Read the current observation schema, collector base class, methodology, source profile template, and legal-risk register before proposing changes.
- Use existing dependencies and test fixtures. Ask before installing packages, changing authentication, enabling schedules, deploying, or publishing data.
- Confirm whether the request is research-only, profile, implementation, or review. Research-only mode must not modify repository files.
Workflow
- Establish repository truth with
GlobandRead: locate the current schema, collector modules, tests, methodology, source-profile convention, provider IDs, and mappings. - Define the requested source and collection boundary: official provider, aggregator, manual submission, or fixture; public page or API; authentication; expected units; intended refresh cadence.
- Research with
WebSearchandWebFetch, preferring the provider's official pricing, API, terms, robots.txt, rate-limit, and changelog pages. Record the exact URL and retrieval time for every claim. - Separate observations from judgments. A reachable endpoint or permissive
robots.txt file is not proof that automated collection or redistribution is
legally authorized. Mark ambiguous terms
LEGAL REVIEW REQUIRED. - Reconcile the proposed source tier against the repository's current written methodology and implementation. Report contradictions instead of silently choosing one; in particular, aggregator classification must be consistent across docs, schema usage, and collector code.
- Produce the evidence and acceptance matrix in the evaluation reference. Stop in profile mode after presenting it.
- In implementation mode, obtain approval for the proposed file set, then use
WriteorEditto add the smallest collector, fixture, profile, and test changes that satisfy the collector contract. - Run the narrow test first, then the repository suite. Use fixture or dry-run
modes before any live collection. Inspect
git diffand report all generated or data-bearing files; do not commit, push, enable CI schedules, deploy, or publish unless explicitly requested.
Approval boundaries
- Proceed: read public documentation; inspect local code and fixtures; draft an evidence packet; run existing local tests.
- Ask first: install dependencies, use credentials, call a metered/private API, write repository files, run a live collection that stores data, or alter source-tier policy.
- Explicit separate authorization: deploy, publish observations, enable a schedule, change cloud/IAM configuration, commit, push, or open a PR.
- Never: scrape around access controls, expose tokens, invent permission from silence, copy restricted content, or label uncertain evidence as verified.
Validation
python -m pytest tests/test_collector.py -v
python -m pytest tests/ -v --tb=short
python -m services.collector.pipeline --fixtures --dry-run
git status --short
git diff --checkValidate every candidate observation against schemas/observation.schema.json
and confirm normalization with fixed input/output unit tests. A live endpoint
response is evidence, not a golden fixture; redact secrets and minimize retained
payloads according to approved policy.
Output
Return:
- mode, source identity, retrieval timestamp, and official evidence URLs;
- auth, rate-limit, automation, and redistribution status, with unknowns clear;
- unit mapping and required observation fields;
- source-tier recommendation plus any policy contradiction;
- proposed or changed files and approval received;
- tests run, exit results, observation counts, and validation failures;
- unresolved legal, operational, provenance, or data-quality risks;
- next human decision, without claiming deployment or publication occurred.
Error Handling
- Terms or permissions unclear: stop before automation and request legal or owner review.
- Authentication required: document the mechanism; never request secrets in chat or place them in code, fixtures, URLs, or logs.
- Rate units ambiguous: retain the raw field and stop normalization until an official definition resolves the unit.
- Schema drift: preserve a minimal redacted sample, report changed fields, and fail closed rather than dropping records silently.
- Rate limit or outage: honor retry guidance; do not retry indefinitely or substitute stale data without the methodology's explicit carry-forward rule.
- Cross-source disagreement: report both values and provenance; do not average or choose a source outside the approved methodology.
- Partial write or failed test: show the diff and failure, preserve evidence, and do not publish.
Examples
Research-only request:
Evaluate Provider X's official pricing API for STCI. Produce evidence and a
source-tier recommendation, but do not edit files or call authenticated APIs.Implementation request:
Using the approved source profile, add the provider collector and fixed fixtures.
Run collector tests and the fixture dry-run; do not deploy or enable schedules.Resources
- Source evidence and acceptance rubric
- Repository-grounded collector contract
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