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Document landscape_query.py in an Available Scripts table with a copy-pasteable invocation and run-when guidance; add Prerequisites and Limitations grounded in the tool's snapshot-based, read-only design. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
CNCF Landscape
Discover cloud-native technologies and turn the result into a decision-ready shortlist with evidence, trade-offs, and a validation plan.
Why Install This Skill
When an architecture question starts with “what exists for this?”, an agent can easily return a familiar-name list or rank projects by stars. This skill gives it a live, source-grounded discovery path through the CNCF Landscape and a disciplined way to separate catalog facts from engineering judgment.
It is useful for architects and engineers exploring a capability that is not yet in their stack. The bundled query tool handles the static API’s filtering and bounded JSON output; the skill then asks the questions the catalog cannot answer: who will operate it, what constraints matter, what evidence is missing, and what small experiment could falsify the recommendation.
What You Get
| Path | Purpose |
|---|---|
SKILL.md |
Trigger boundaries, query workflow, evidence discipline, and completion criteria |
scripts/landscape_query.py |
Read-only stdlib CLI for live project/member queries and local filtering |
references/api.md |
Verified endpoint map, field semantics, and static-site caveats |
references/decision-framework.md |
Candidate comparison and recommendation method |
references/output-template.md |
Reusable decision artifact structure |
tests/test_landscape_query.py |
Offline client and filter tests |
evals/evals.json |
Six output-quality cases covering normal and failure paths |
evals/trigger-queries.json |
Three should-trigger and two should-not-trigger routing probes |
Quick Start
Requires Python 3.8+ and outbound HTTPS access. No API key is required.
python3 scripts/landscape_query.py \
--category "Observability and Analysis" \
--subcategory Observability \
--search tracing \
--maturity graduated \
--has-license --has-release \
--sort stars --limit 10
The command emits a JSON envelope containing the source endpoint, retrieval time, filters, counts, and matching records. Ask an Agent Skills-compatible assistant to interpret that evidence against your workload and constraints rather than treating the result as an automatic ranking.
Triggers
Use when discovering or comparing CNCF/cloud-native projects, building a shortlist for an architecture decision, filtering technology candidates by maturity or repository evidence, or investigating what tools exist for a capability missing from the current stack.
Do not use it for operating a named project, general architecture methodology, or legal/procurement conclusions.
Requirements
- Python 3.8 or newer
- Network access to
https://landscape.cncf.io - No credentials or third-party Python packages