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weather

Get current weather and forecasts (no API key required).

63

Quality

76%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./raven/memory_engine/skills/weather/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

92%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is an exemplary lean skill: immediately executable curl commands with sample outputs, a sensible primary/fallback split, and clean section organization with no token waste. The only notable gap is that the Open-Meteo fallback assumes the user can already find coordinates without showing how. It scores near the top of the rubric overall.

DimensionReasoningScore

Conciseness

The body is lean and assumes competence: no explanations of what weather APIs are, no padding, and every line is a command, expected output, format code, or tip. It matches the anchor for lean, efficient content where every token earns its place.

5 / 5

Actionability

The wttr.in section is fully copy-paste ready with expected outputs ("curl -s \"wttr.in/London?format=3\"" → "London: ⛅️ +8°C") plus a concrete fallback command for Open-Meteo. It stops short of 5 because the fallback section says "Find coordinates for a city, then query" without showing a concrete geocoding step, a minor gap in executability.

4 / 5

Workflow Clarity

This is a simple, single-purpose skill under 50 lines with no destructive or batch operations, and the single action is unambiguous: primary service with a quick one-liner, clearly labeled fallback ("## Open-Meteo (fallback, JSON)") for programmatic use. Per the simple-skill guidance, workflow clarity scores 5.

5 / 5

Progressive Disclosure

The skill is under 50 lines, needs no external references, and is organized into well-labeled sections (quick one-liner, compact format, full forecast, tips, fallback) with a docs link for depth. Per the guideline for short simple skills, well-organized sections earn a 5.

5 / 5

Total

19

/

20

Passed

Description

61%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is concise, in an appropriate imperative voice, and clearly communicates what the skill does, with a helpful differentiator ("no API key required"). Its main weakness is the missing "Use when..." trigger guidance, which caps completeness, alongside only two stated capabilities and thin synonym coverage. Adding an explicit use-when clause and a couple more natural trigger terms would lift it substantially.

Suggestions

Add an explicit trigger clause, e.g., "Use when the user asks about weather, forecasts, temperature, or conditions in a location."

Broaden trigger-term coverage with natural synonyms such as "temperature", "rain", or "how hot/cold" so it matches more phrasings users actually say.

Mention one or two more concrete capabilities in the description (e.g., location lookup by city or airport code, JSON output for programmatic use) to strengthen specificity.

DimensionReasoningScore

Specificity

"Get current weather and forecasts" names the domain plus two concrete capabilities (current conditions, forecasts), matching the anchor for 1-2 concrete actions without comprehensive coverage. It does not reach 4 because no additional actions (e.g., units, location lookup, programmatic JSON access) are listed, and it is above 2 because the actions are concrete rather than generic.

3 / 5

Completeness

The "what" is clearly stated ("Get current weather and forecasts") but there is no "Use when..." clause or equivalent explicit trigger guidance, which caps completeness at 3 per the judging guidelines. It is not 4 because the "when" is entirely absent rather than merely imprecise.

3 / 5

Trigger Term Quality

"current weather" and "forecasts" are the natural phrases users say for this need, giving good keyword coverage. It falls short of 5 because common synonyms and variations like "temperature", "rain", or "how hot is it" are absent, but sits above 3 because the core natural terms are present.

4 / 5

Distinctiveness Conflict Risk

Weather lookup is a clear niche with low overlap risk against other skills, and "(no API key required)" further distinguishes its approach. It stays at 4 rather than 5 because the trigger set is sparse (no distinct trigger phrases beyond "weather"/"forecasts"), leaving minor overlap risk with other data-lookup skills.

4 / 5

Total

14

/

20

Passed

Validation

81%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

13

/

16

Passed

Repository
EverMind-AI/Raven
Reviewed

Table of Contents

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