Borrowing it
Nothing to install: this file belongs to lostnumber07/shearline. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lostnumber07/shearline/main/.claude/skills/chase-day-briefing/SKILL.mdgit clone --depth 1 https://github.com/lostnumber07/shearlineWrote 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/skills/lostnumber07/shearline/chase-day-briefing)<a href="https://agentmods.dev/skills/lostnumber07/shearline/chase-day-briefing"><img src="https://agentmods.dev/badge/skills/lostnumber07/shearline/chase-day-briefing/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lostnumber07/shearline/chase-day-briefing"><img src="https://agentmods.dev/badge/skills/lostnumber07/shearline/chase-day-briefing.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00069 | $0.00753 |
| Opus 5.5 | $0.00028 | $0.00301 |
| Sonnet 5.5 | $0.00014 | $0.00151 |
| Haiku 4.5 | $0.00007 | $0.00075 |
Grade A, and why
chase-day-briefing 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 2mo ago.
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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chase-day briefing
Goal: a concise field briefing for a target point today — what's expected, is the environment loaded and trending up, is anything already happening, and a clear go / hold / no-go with the window of greatest concern.
Reminder: SHEARLINE is decision support. Official NWS watches/warnings drive life-safety decisions; say so in the briefing.
Inputs you need
- Target —
lat, lon(CONUS). For a region, pick the centroid or run the sequence for two or three candidate points.
Procedure (run in this order; the later steps refine the earlier)
-
The forecast frame.
get_spc_outlook(lat, lon, day=1)- Note
data.categorical.label(MRGL→HIGH) and the tornado/hail/windprobabilities. If you're planning ahead, alsoday=2.
- Note
-
The environment now.
get_point_environment(lat, lon)- Read the
interpretation— it names the regime (pulse / cool-season high-shear / classic supercell). Note MLCAPE, 0–6 km shear, 0–1 km SRH, SCP, effective STP, and whether instability is capped (large negative MLCIN matters — storms may not fire until the cap erodes).
- Read the
-
The trajectory.
get_environment_trend(lat, lon)- This is the chase-critical step: is STP/CAPE rising into the afternoon, or
stabilizing? Read the trend
interpretation("intensifying" vs "weakening").
- This is the chase-critical step: is STP/CAPE rising into the afternoon, or
stabilizing? Read the trend
-
What's already up.
get_active_warnings(lat, lon, radius_km=80)andget_mrms_severe(lat, lon, radius_km=80)- Any active warnings, and any MESH / rotation-track signatures already in range (storms upstream that will move toward the target).
-
Synthesize. Optionally run
get_threat_brief(lat, lon)for the composite level, then write the call.
Output template
Chase briefing — (<lat>, <lon>), <date>
Outlook: SPC <category>; tornado <x>% / hail <y>% / wind <z>%
Environment: <regime in one phrase>; MLCAPE <..> J/kg, 0-6km shear <..> kt,
0-1km SRH <..>, eff-STP <..>, SCP <..>; cap: <none/weak/strong>
Trend (f00→f06): <intensifying | steady | weakening> — <one line>
Already active: <warnings / MESH / rotation in range, or "nothing yet">
CALL: <GO | HOLD | NO-GO>
Target window: <e.g. 21–01Z as heating maximizes / cap erodes>
Watch for: <the single signal that would change the call, e.g.
"rotation track appearing within 60 km to the SW">
Safety: follow live NWS warnings; this is planning support only.
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.
- 2mo ago First seen · 58 lines · 69 tokens per session scan A 6b84835a66d2
chase-day-briefing is a skill published in the GitHub repository lostnumber07/shearline (1 stars, last pushed 1mo ago), licensed MIT. It adds 69 tokens to every session and 753 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
chase-day-briefing compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| chase-day-briefinglostnumber07/shearline | Skill | 1 | 1mo ago | MIT | A | 69 | Claude Code |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 2d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |