nws-weather-forecast
Skill97 starsChanged 34 days agoApache-2.0View on GitHub
Fetch National Weather Service forecast evidence through the governed HTTP front, producing a sealed provider packet for downstream weather planning.
In this repository94 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- llms.txtllms.txt
- runxSkill
- adopt-skillSkill
- agencySkill
- answer-from-docsSkill
- attention-reviewSkill
- audit-receiptSkill
- brand-voiceSkill
- business-opsSkill
- chargeSkill
- chief-of-staffSkill
- cold-outreachSkill
- content-pipelineSkill
- contract-drafterSkill
- conversation-replySkill
- conversation-reviewSkill
- crm-cleanupSkill
- cve-auditSkill
- data-storeSkill
- data-subject-requestSkill
- deep-researchSkill
- diagnose-skill-runSkill
- dispute-respondSkill
- ecosystem-briefSkill
- extractSkill
- ghostwriteSkill
- github-pr-commentSkill
- github-pr-reviewSkill
- github-syncSkill
- google-analyticsSkill
- google-calendarSkill
- google-search-consoleSkill
- governed-outboundSkill
- helpdeskSkill
- incident-commanderSkill
- issue-intakeSkill
- issue-to-prSkill
- issue-triageSkill
- knowledge-routerSkill
- lead-enrichmentSkill
- lead-qualifySkill
- least-privilegeSkill
- ledgerSkill
- list-hygiene-judgeSkill
- marketplace-invokeSkill
- meeting-followupSkill
- mock-chargeSkill
- mock-paySkill
- mock-refundSkill
- moltbookSkill
- n8n-handoffSkill
- nitrosendSkill
- open-meteo-weather-forecastSkill
- operator-inboxSkill
- ops-deskSkill
- organic-growthSkill
- policy-authorSkill
- postmortem-makerSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
8 rules. About 0 are common, 1 is distinctive, and 7 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
7
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 13
No API key is required. The default runner fetches the actual NWS gridpoint forecast.
- Very specific: line 46
If the caller has only coordinates, run locate with lat and lon.
- Very specific: line 48
Run the default forecast runner with office, grid_x, and grid_y.
- Very specific: line 51
If an agent needs planning prose, pass the provider evidence to weather-forecast.
- Distinctive: line 67
Action requested from weather: stop at provider evidence and require the downstream action skill with its own gate and receipt.
- Very specific: line 92
Run locate for 38.8894,-77.0352.
- Very specific: line 95
Run the default forecast runner with office: LWX, grid_x: "97", grid_y: "71".
- Very specific: line 97
Use the sealed forecast JSON as forecast_evidence for weather-forecast when a downstream agent needs a planning packet.
≈ “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
NWS Weather Forecast
Fetch public National Weather Service forecast evidence through runx HTTP.
This is a branded provider skill for the canonical weather-forecast verb. It
uses the governed HTTP front, not an ad hoc client: the receipt records the NWS
endpoint, response status, graph step receipts, and the exact authority surface.
No API key is required. The default runner fetches the actual NWS gridpoint
forecast; the locate runner discovers the gridpoint for a latitude/longitude.
What this skill does
nws-weather-forecast makes read-only calls to api.weather.gov. The locate
runner calls /points/{lat},{lon} to discover gridId, gridX, gridY, and
forecast URLs. The default forecast runner calls
/gridpoints/{office}/{grid_x},{grid_y}/forecast to fetch forecast periods. The
output is provider evidence; use weather-forecast when an agent needs to
normalize that evidence for a planning decision.
When to use this skill
- You need real public weather evidence with no credentials.
- A graph needs to prove a weather data read went through runx's governed HTTP path.
- You have an NWS office/gridpoint and need the current public forecast.
- You have latitude and longitude in the United States and need the NWS gridpoint before running the forecast path.
When not to use this skill
- For locations outside NWS coverage. Return
needs_inputwith the coverage limitation. - For emergency, medical, aviation, maritime, evacuation, or life-safety decisions.
- To notify users, reschedule events, deploy changes, or mutate operations based on weather. Those actions need their own authority gate.
- To call private networks, untrusted hosts, or non-NWS endpoints.
Procedure
- If the caller has only coordinates, run
locatewithlatandlon. - Extract
gridId,gridX, andgridYfrom the sealed locate output. - Run the default
forecastrunner withoffice,grid_x, andgrid_y. - Confirm the HTTP status is 2xx and the response contains forecast periods.
- Preserve the NWS source URL, generated timestamp, gridpoint, and receipt refs.
- If an agent needs planning prose, pass the provider evidence to
weather-forecast. Do not invent guidance inside this provider fetch. - Return
needs_inputfor malformed coordinates or gridpoints; returnneeds_more_evidencefor NWS outages, missing periods, or stale data.
Edge cases and stop conditions
- Invalid coordinates: return
needs_input; NWS point lookup requires decimal latitude and longitude. - Unsupported location: return
needs_input; NWS coverage is not global. - Provider outage or non-2xx response: return
needs_more_evidenceand preserve the HTTP status in the receipt. - Missing forecast periods: return
needs_more_evidence; do not summarize a forecast that is not present. - Life-safety use: return
refusedand direct the user to official weather or emergency channels. - Action requested from weather: stop at provider evidence and require the downstream action skill with its own gate and receipt.
Output schema
decision: ready | needs_input | needs_more_evidence | refused
canonical_skill: runx/weather-forecast
runtime_path: http
provider: national-weather-service
provider_evidence:
endpoint: string
http_status: string
gridpoint:
office: string
grid_x: string
grid_y: string
generated_at: string
forecast_periods: array
receipt_refs: array
stop_conditions: arrayWorked example
- Run
locatefor38.8894,-77.0352. - The sealed NWS points response returns
gridId: LWX,gridX: 97,gridY: 71, and a forecast URL. - Run the default
forecastrunner withoffice: LWX,grid_x: "97",grid_y: "71". - Use the sealed forecast JSON as
forecast_evidenceforweather-forecastwhen a downstream agent needs a planning packet.
Inputs
office(default runner, required): NWS office id such asLWX.grid_x(default runner, required): NWS grid X coordinate.grid_y(default runner, required): NWS grid Y coordinate.lat(locaterunner, required): decimal latitude for point lookup.lon(locaterunner, required): decimal longitude for point lookup.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

