Borrowing it
Nothing to install: this file belongs to scitex-ai/claude-code-telegrammer. 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/scitex-ai/claude-code-telegrammer/main/.claude/skills/quality-guards/SKILL.mdgit clone --depth 1 https://github.com/scitex-ai/claude-code-telegrammerWrote 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/scitex-ai/claude-code-telegrammer/quality-guards)<a href="https://agentmods.dev/skills/scitex-ai/claude-code-telegrammer/quality-guards"><img src="https://agentmods.dev/badge/skills/scitex-ai/claude-code-telegrammer/quality-guards/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/scitex-ai/claude-code-telegrammer/quality-guards"><img src="https://agentmods.dev/badge/skills/scitex-ai/claude-code-telegrammer/quality-guards.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 | $0.00036 | $0.00568 |
| Opus 5.5 | $0.00014 | $0.00227 |
| Sonnet 5.5 | $0.00007 | $0.00114 |
| Haiku 4.5 | $0.00004 | $0.00057 |
Grade C, and why
quality-guards scanned grade C 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 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
| Filesystem | `rm -rf`, `rm -r` on data directories, bulk deletes | The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- 2mo ago First seen · 58 lines · 36 tokens per session scan C b61453953e39
quality-guards is a skill published in the GitHub repository scitex-ai/claude-code-telegrammer (1 stars, last pushed 9d ago), licensed AGPL-3.0. It adds 36 tokens to every session and 568 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
gh-pr-review
Review GitHub Pull Requests using the gh CLI. Use when a user asks to review a PR, perform code review, check a pull request, or provide feedback on proposed changes. Triggers on phrases like "review PR", "review pull request", "check PR", "code review".
code-review
Provides expert code review guidelines and best practices.
audit
Security and quality audit of application codebase.
bridgebuilder-review
Bridgebuilder — Autonomous PR Review.
diagnose
Deep investigation of a single construct. Identity-reality drift, maintenance pattern, composition analysis.
autoreview
Structured code review through the shared OpenClaw agent-skills installation.