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 Abilityai/abilities --skill bug-reportgit clone --depth 1 https://github.com/Abilityai/abilitiesWrote 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/abilityai/abilities/bug-report)<a href="https://agentmods.dev/skills/abilityai/abilities/bug-report"><img src="https://agentmods.dev/badge/skills/abilityai/abilities/bug-report/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/abilityai/abilities/bug-report"><img src="https://agentmods.dev/badge/skills/abilityai/abilities/bug-report.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 | $0.00053 | $0.01435 |
| Opus 5.5 | $0.00021 | $0.00574 |
| Sonnet 5.5 | $0.00011 | $0.00287 |
| Haiku 4.5 | $0.00005 | $0.00144 |
Grade A, and why
bug-report scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bug Report
ℹ️ First, set expectations: before anything else, print one short line with this skill's version and its most recent change — the top entry of
metadata.changelogabove — e.g.bug-report vX.Y — recent: <summary>. Then proceed.
Create a well-structured GitHub issue from an incident or observed bug. Automatically sanitizes sensitive data before submission so it's safe to post to a public or shared repository.
Prerequisites
Requires gh CLI authenticated and configured:
gh auth status
The target repository should be set in the environment or prompted:
GITHUB_REPO=${GITHUB_REPO:-""} # e.g. "org/repo"
Step 1: Gather Bug Information
Read from $ARGUMENTS or ask the user:
- Title: Short description of the bug (1 line)
- Source: From a recent incident report? From observation? From logs?
- Repo: Which GitHub repo to file against
If an incident report file exists (e.g. incidents/*.md), offer to use it as input:
ls incidents/*.md 2>/dev/null | sort -r | head -5
Step 2: Collect Raw Content
If based on an incident report, read it:
# Read most recent incident report
LATEST=$(ls incidents/*.md 2>/dev/null | sort -r | head -1)
cat "$LATEST"
Otherwise, ask the user to paste or describe:
- Observed behavior
- Expected behavior
- Steps to reproduce
- Relevant error messages or log snippets
- Environment (OS, version, config)
Step 3: Sanitize Sensitive Data
Before writing the issue, replace all sensitive data with safe placeholders.
Redaction rules:
| Pattern | Replace with |
|---|---|
| Private IP addresses (10.x, 172.16-31.x, 100.x, 192.168.x) | [INTERNAL-IP] |
| Public IP addresses | [REDACTED-IP] |
| Tailscale IPs (100.x.x.x) | [TAILSCALE-IP] |
API keys, tokens, secrets (anything matching key=..., token=..., secret=..., password=..., Bearer ...) |
[REDACTED-SECRET] |
| SSH private key content | [REDACTED-KEY] |
| Email addresses of users | [USER-EMAIL] |
Full filesystem paths with usernames (e.g. /home/alice/) |
replace username with [USER] |
| Database connection strings | [REDACTED-DB-URL] |
| Instance-specific hostnames or subdomains | [INSTANCE-HOSTNAME] |
| GCP project IDs | [GCP-PROJECT] |
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.
- 1mo ago First seen · 221 lines · 53 tokens per session scan A 684493b73a6d
bug-report is a skill published in the GitHub repository Abilityai/abilities (12 stars, last pushed 3d ago), licensed MIT. It adds 53 tokens to every session and 1,435 once invoked, about $0.0002 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 2026-09-07.
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