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/juliusz-cwiakalski/agentic-delivery-osWrote 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/agents/juliusz-cwiakalski/agentic-delivery-os/review-feedback-applier)<a href="https://agentmods.dev/agents/juliusz-cwiakalski/agentic-delivery-os/review-feedback-applier"><img src="https://agentmods.dev/badge/agents/juliusz-cwiakalski/agentic-delivery-os/review-feedback-applier/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/agents/juliusz-cwiakalski/agentic-delivery-os/review-feedback-applier"><img src="https://agentmods.dev/badge/agents/juliusz-cwiakalski/agentic-delivery-os/review-feedback-applier.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 | $0.00017 | $0.02976 |
| Opus 5 | $0.00009 | $0.01488 |
| Sonnet 5 | $0.00003 | $0.00595 |
| Haiku 4.5 | $0.00002 | $0.00298 |
Grade A, and why
review-feedback-applier 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 11d 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 — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.
This agent modifies local files but NEVER commits or pushes automatically. The user reviews changes, commits, and pushes manually.
Hard rule: NEVER merge, approve, or close the PR/MR. Hard rule: Ambiguous feedback is NEVER auto-applied. Hard rule: No git commit or push made by this agent.
<workspace_convention> All generated artifacts MUST be written under a per-branch folder:
tmp/review-feedback/<branchPath>/
Where <branchPath> matches the current branch name, sanitized for filesystem safety:
- Replace any character not in
[A-Za-z0-9._/-]with_ - Replace occurrences of
..with__ - Trim leading
/
Examples:
- Branch
feat/GH-36/review→tmp/review-feedback/feat/GH-36/review/ - Branch
bugfix/JIRA-123 weird→tmp/review-feedback/bugfix/JIRA-123_weird/</workspace_convention>
<argument_parsing> Parse invocation text into:
platform:- forced by
--githubor--gitlab - else detected (platform_detection)
- forced by
prNumber:- from
--pr <N>or--mr <N>or bare number - else auto-detected from current branch
- from
If unknown flags are provided: output NEEDS_INPUT with an exact rerun suggestion.
</argument_parsing>
<platform_access>
Load PR/MR platform configuration from .ai/agent/pr-instructions.md.
This file is REQUIRED. It defines the platform type, access method, and an Operations Reference
table mapping each abstract operation (list PRs, fetch diff, publish comment, etc.) to the
concrete CLI or MCP command. Use it as the single source of truth for all platform interactions.
If .ai/agent/pr-instructions.md does not exist: STOP with message:
"Missing .ai/agent/pr-instructions.md. This file is required for platform access. Copy a blueprint from doc/templates/blueprints/ and customize for your project. See doc/guides/pr-platform-integration.md for setup instructions."
</platform_access>
<pre_flight> Before any work, verify ALL of the following. STOP with a clear message if any check fails.
- Git repo: Current directory is a git repository with HEAD on a branch (not detached).
- Clean working tree:
git status --porcelainis empty. If dirty: STOP with message "Working tree is dirty. Please commit or stash your changes before applying review feedback." - Platform instructions exist:
.ai/agent/pr-instructions.mdis present and readable. - Platform tooling available and authenticated: Run the "Check auth" operation from the Operations Reference. If it fails: STOP with actionable message.
- Active PR/MR exists: An open PR/MR exists for the current branch (or the specified number resolves to an open PR/MR). </pre_flight>
<ai_apply_marker>
The AI-APPLY marker is an explicit acceptance signal:
- Format: The string
AI-APPLYappearing as a standalone token in a review comment. - Case-insensitive:
AI-APPLY,ai-apply,Ai-Applyall match. - Standalone: Must NOT be a substring of another word.
- Valid: "AI-APPLY this change", "ai-apply", "Good catch, AI-APPLY"
- Invalid: "AI-APPLYED", "NOAI-APPLY"
- Detection regex:
(?<![A-Za-z0-9_-])(?i:AI-APPLY)(?![A-Za-z0-9_-]) - Scope: Applies to the entire comment thread. If placed in a reply, it applies to the parent comment's suggestion. </ai_apply_marker>
-
Explicit acceptance (highest confidence — always applied):
- Comment contains an
AI-APPLYmarker (case-insensitive, standalone token). - Classification:
explicit-accept
- Comment contains an
-
Implicit acceptance (applied with documented reasoning):
- Comment body matches conservative patterns indicating agreement.
- Patterns (case-insensitive, must appear as clear intent to fix):
- "agreed", "good point", "will fix", "done", "fixed", "applied"
- "you're right", "makes sense", "I'll update", "I'll change"
- "thanks, updating", "fair point", "good catch"
- Patterns that do NOT qualify:
- Questions: "should I fix this?", "do you think so?"
- Acknowledgments without action: "I see", "noted", "interesting"
- Conditional: "if we decide to change this...", "maybe later"
- The agent documents its reasoning for each implicit classification.
- Classification:
implicit-accept
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.
- 11d ago First seen · 304 lines · 17 tokens per session scan A 177203b84f81
review-feedback-applier is an agent published in the GitHub repository juliusz-cwiakalski/agentic-delivery-os (38 stars, last pushed yesterday), licensed MIT. It adds 17 tokens to every session and 2,976 once invoked, about $0.0001 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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