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 WaterplanAI/agentic-config --skill ac-tools-ac-issuegit clone --depth 1 https://github.com/WaterplanAI/agentic-configWrote 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/waterplanai/agentic-config/ac-tools-ac-issue)<a href="https://agentmods.dev/skills/waterplanai/agentic-config/ac-tools-ac-issue"><img src="https://agentmods.dev/badge/skills/waterplanai/agentic-config/ac-tools-ac-issue/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/waterplanai/agentic-config/ac-tools-ac-issue"><img src="https://agentmods.dev/badge/skills/waterplanai/agentic-config/ac-tools-ac-issue.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 | $0.00040 | $0.02706 |
| Opus 5 | $0.00020 | $0.01353 |
| Sonnet 5 | $0.00008 | $0.00541 |
| Haiku 4.5 | $0.00004 | $0.00271 |
Grade A, and why
ac-tools-ac-issue scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 402 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Issue Reporter
Compatibility Note
This pi wrapper preserves the original issue-reporting workflow while replacing the legacy plugin-root version lookup with a current-checkout VERSION fallback when available.
Creates GitHub issues in the central agentic-config repository (WaterplanAI/agentic-config) for bug reports and feature requests.
Usage
/skill:ac-tools-ac-issue # Context-based: extract from conversation
/skill:ac-tools-ac-issue "Title" "Description" # Explicit: user provides details
/skill:ac-tools-ac-issue --bug "Title" # Bug report with template
/skill:ac-tools-ac-issue --feature "Title" # Feature request with template
Target Repository: WaterplanAI/agentic-config
Workflow Steps
Step 1: Authentication Verification (CRITICAL - DO FIRST)
INSTRUCTION: Verify GitHub CLI authentication before any other operation.
# Check if gh CLI is installed
if ! GH_BIN=$(command -v gh); then
echo "ERROR: GitHub CLI (gh) not found"
echo ""
echo "Please install GitHub CLI: https://cli.github.com/"
exit 1
fi
echo "Checking GitHub CLI authentication..."
GH_AUTH_OUTPUT=$("$GH_BIN" auth status 2>&1)
GH_AUTH_STATUS=$?
if [ $GH_AUTH_STATUS -ne 0 ]; then
echo "ERROR: GitHub CLI not authenticated"
echo ""
echo "$GH_AUTH_OUTPUT"
echo ""
echo "Please authenticate with: gh auth login"
exit 1
fi
echo "$GH_AUTH_OUTPUT"
echo ""
echo "Authentication verified."
Validation Logic:
- Run
gh auth statusand capture exit code - If exit code != 0: STOP immediately with error and
gh auth logininstruction - If authenticated: Continue with success message
Step 2: Input Mode Detection
INSTRUCTION: Parse arguments to determine input mode.
Arguments: $ARGUMENTS
Mode Detection Logic:
| Input Pattern | Mode | Action |
|---|---|---|
| Empty/no args | Context Mode | Extract from recent conversation |
--bug "Title" |
Bug Template | Use bug report template with provided title |
--feature "Title" |
Feature Template | Use feature request template with provided title |
"Title" "Description" |
Explicit Mode | Use provided title and description |
"Title" only |
Explicit Mode | Use title, prompt for description |
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 · 402 lines · 40 tokens per session scan A 74eca4dd4913
ac-tools-ac-issue is a skill published in the GitHub repository WaterplanAI/agentic-config (30 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 2,706 once invoked, about $0.0002 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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