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 davidmigloz/ai_clients_dart --skill upskillgit clone --depth 1 https://github.com/davidmigloz/ai_clients_dartWrote 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/davidmigloz/ai_clients_dart/upskill)<a href="https://agentmods.dev/skills/davidmigloz/ai_clients_dart/upskill"><img src="https://agentmods.dev/badge/skills/davidmigloz/ai_clients_dart/upskill/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/davidmigloz/ai_clients_dart/upskill"><img src="https://agentmods.dev/badge/skills/davidmigloz/ai_clients_dart/upskill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Rogue Agent · line 4 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
- high Rogue Agent · line 205 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
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 | $0.00078 | $0.03163 |
| Opus 5 | $0.00039 | $0.01581 |
| Sonnet 5 | $0.00016 | $0.00633 |
| Haiku 4.5 | $0.00008 | $0.00316 |
Grade A, and why
upskill 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 9d 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 — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Upskill Skill for ai_clients_dart
This skill automates the feedback loop from PR reviews to skill files. It extracts validated review findings (comments marked **Valid.** by the PR author), consolidates them into generalizable patterns, and updates the review checklists and implementation pattern files to prevent recurring issues.
Parse $ARGUMENTS for options:
/upskill— Full apply mode (no flags). Runs the complete workflow (Steps 1–9), updating files and state after confirmation.--plan— Extract and analyze findings without editing any files. Safe to run anytime.--dry-run— Run the full apply workflow (extraction, consolidation, validation, proposed updates) but stop before actually editing files. Shows exactly what would change without changing anything.--from N— Start after PR number N instead of the config'slast_checked_pr.
Step 1: Validate Environment
Perform all checks before proceeding. Fail fast with an actionable error message if any check fails.
- CLI availability:
git,gh, andjqmust be on PATH. - GitHub auth:
gh auth statusmust show authenticated. - Repository root: Use
git rev-parse --show-toplevelto determine the repo root. All file paths are relative to this root.
Note: The Bash tool does not persist
cdacross calls. Prefix all shell commands withcd "$REPO_ROOT" &&or use absolute paths.
- Rate limit: Check remaining API calls:
If remaining < 100, warn the user and stop — the extraction phase makes many API calls.gh api rate_limit --jq '.rate.remaining'
Step 2: Determine PR Range
- Read
.agents/skills/upskill/config/state.json:{ "last_checked_pr": 122, "last_run_date": "2026-03-19" }Note: On the very first run,
last_run_datewill benull. In this case, rely solely onlast_checked_prto determine the PR range. - If the file does not exist or is unreadable, default
last_checked_prto0and warn: "No state file found — this is a first run, scanning all merged PRs." - If
--from Nwas provided, overridelast_checked_prwith N. - Set
START_PRto the effective starting PR number: use the--from Nvalue if provided, otherwiselast_checked_prfrom state. - Record the starting PR number for the summary.
What ships with it
1 file 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.
- 9d ago First seen · 280 lines · 78 tokens per session scan A 2d9f3fcb8735
upskill is a skill published in the GitHub repository davidmigloz/ai_clients_dart (24 stars, last pushed today), licensed MIT. It adds 78 tokens to every session and 3,163 once invoked, about $0.0004 per session on Opus 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 2026-08-30.
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