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.
git clone --depth 1 https://github.com/ccplugins/awesome-claude-code-pluginsWrote 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/commands/ccplugins/awesome-claude-code-plugins/skip-reflect)<a href="https://agentmods.dev/commands/ccplugins/awesome-claude-code-plugins/skip-reflect"><img src="https://agentmods.dev/badge/commands/ccplugins/awesome-claude-code-plugins/skip-reflect/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/commands/ccplugins/awesome-claude-code-plugins/skip-reflect"><img src="https://agentmods.dev/badge/commands/ccplugins/awesome-claude-code-plugins/skip-reflect.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 | $0.00006 | $0.00242 |
| Opus 5.5 | $0.00002 | $0.00097 |
| Sonnet 5.5 | $0.00001 | $0.00048 |
| Haiku 4.5 | $0.00001 | $0.00024 |
Grade A, and why
skip-reflect 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.
What it actually says
Context
- Queue count: !
jq 'length' ~/.claude/learnings-queue.json 2>/dev/null || echo 0
Your Task
-
If queue is empty:
- Output: "Queue is already empty. Nothing to skip."
- Exit
-
If queue has items:
- Show: "You are about to discard [count] learning(s). These will be lost:"
- List each queued item briefly (type + first 50 chars of message)
- Ask: "Are you sure? [y/n]"
-
If user confirms (y/yes):
- Clear the queue:
echo "[]" > ~/.claude/learnings-queue.json- Output: "Discarded [count] learnings. Queue cleared."
-
If user declines (n/no):
- Output: "Aborted. Run /reflect to process learnings instead."
Note
This is an escape hatch for when auto-detection captures false positives or learnings aren't worth saving. Use sparingly.
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 · 33 lines · 6 tokens per session scan A 6d9a1161ead1
skip-reflect is a command published in the GitHub repository ccplugins/awesome-claude-code-plugins (977 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 6 tokens to every session and 242 once invoked, about $0.0000 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 2026-09-03.
Other commands, from other repositories
create-pull-request
Provides comprehensive PR creation guidance with GitHub CLI, enforcing title conventions, following template structure, and offering concrete command examples with best practices.
pr-issue-resolve
Follow these steps to analyze suggested changes (e.g., review comments, inline suggestions, or requested modifications) in a GitHub Pull Request (PR) and resolve them efficiently. The goal is to review, understand, plan fixes, apply changes, test, and update the PR while maintaining code quality and collaboration.
openapi-expert
Use this agent when you need to update, synchronize, or validate the OpenAPI specification (openapi.yml) against the actual REST API implementation. This includes adding new endpoints, updating request/response schemas, fixing discrepancies between the spec and code, or ensuring complete API documentation coverage.
husky
Sets up and manages Husky Git hooks by configuring pre-commit hooks, establishing commit message standards, integrating with linting tools, and ensuring code quality on commits.
pr-review
Reviews pull request changes to provide feedback, check for issues, and suggest improvements before merging into the main codebase.
create-pr
Streamlines pull request creation by handling the entire workflow: creating a new branch, committing changes, formatting modified files with Biome, and submitting the PR.