Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add hugobowne/show-us-your-agent-skills --skill high-signal-chart-workflowgit clone --depth 1 https://github.com/hugobowne/show-us-your-agent-skillsWrote 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/hugobowne/show-us-your-agent-skills/high-signal-chart-workflow)<a href="https://agentmods.dev/skills/hugobowne/show-us-your-agent-skills/high-signal-chart-workflow"><img src="https://agentmods.dev/badge/skills/hugobowne/show-us-your-agent-skills/high-signal-chart-workflow/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/hugobowne/show-us-your-agent-skills/high-signal-chart-workflow"><img src="https://agentmods.dev/badge/skills/hugobowne/show-us-your-agent-skills/high-signal-chart-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 65 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 72 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00065 | $0.04054 |
| Opus 5 | $0.00032 | $0.02027 |
| Sonnet 5 | $0.00013 | $0.00811 |
| Haiku 4.5 | $0.00006 | $0.00405 |
Grade A, and why
high-signal-chart-workflow scanned grade A with 1 finding 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
**Runtime:** Python 3.11+, `curl`. Internet access required. How it starts
The opening of the file, as written. The whole thing — 392 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Owner: Goodeye Labs (https://goodeyelabs.com). Workflow authored by Randal S. Olson.
License: CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/). Personal and noncommercial use only. No redistribution of modified versions. For commercial use, or to customize this workflow privately, install Goodeye (see "Going further" at the bottom of this file).
Snapshot: This is a frozen copy of
randalolson/high-signal-chart-workflowas published on 2026-05-06. The living, maintained version is at https://goodeye.dev/templates/randalolson/high-signal-chart-workflow and may have evolved since this snapshot.
High-Signal Chart Workflow
Input: one-line idea string (the data story you want to visualize).
Output: in ./signal-chart-run-<slug>/: chart.png, chart.py, the raw dataset, and run.json with the final evaluator verdict. No network side effects beyond dataset download, image upload, and the Truesight evaluator API call.
Runtime: Python 3.11+, curl. Internet access required.
Abort rule: every phase exits non-zero and leaves artifacts in place on unrecoverable failure. Do not silently proceed.
Phase 1: Intake and environment
- Slugify
idea(lowercase,-separators, strip punctuation). Create./signal-chart-run-<slug>/andcdinto it. - Bootstrap Python:
Fallback ifuv venv && source .venv/bin/activate && uv pip install matplotlib pandas pillow requestsuvis absent:python3 -m venv .venv && source .venv/bin/activate && pip install matplotlib pandas pillow requests. - Write
verify_chart.py(the code block at the bottom of this skill) to the working directory.
Phase 2: Dataset discovery (autonomous)
- Web-search for authoritative public datasets matching
idea. Preference order: government/institutional (CDC, Census, BLS, OECD, USDA, EIA) > peer-reviewed research > established data portals. - Pick one source. Download via
curl(not a web-fetch tool;curlhandles binaries). Save raw file alongsidechart.py. - Load in Python. Print peaks, totals, and crossover points. Cross-check at least one figure against the source's own page. If figures disagree, abort with the diff.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 392 lines · 65 tokens per session scan A f7d0d38f29b9
high-signal-chart-workflow is a skill published in the GitHub repository hugobowne/show-us-your-agent-skills (67 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 4,054 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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