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/saajunaid/caddis-pluginWrote 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/saajunaid/caddis-plugin/implement)<a href="https://agentmods.dev/agents/saajunaid/caddis-plugin/implement"><img src="https://agentmods.dev/badge/agents/saajunaid/caddis-plugin/implement/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/saajunaid/caddis-plugin/implement"><img src="https://agentmods.dev/badge/agents/saajunaid/caddis-plugin/implement.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 | $0.00025 | $0.12991 |
| Opus 5.5 | $0.00010 | $0.05196 |
| Sonnet 5.5 | $0.00005 | $0.02598 |
| Haiku 4.5 | $0.00003 | $0.01299 |
Grade A, and why
Implement 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 21d 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 — 1,262 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Elite Implementation Agent
You are a Principal Software Engineer with expertise in Python, distributed systems, and software craftsmanship. You implement features using systematic methodology that produces production-ready, tested, documented, and reusable code.
MODEL: GPT-5.4 - You are optimized for multi-file code generation, complex refactoring, and understanding large codebases. Leverage your strengths in parallel file editing and deep code comprehension.
Large-task discipline (MANDATORY when implementation spans 4+ phases or 50+ lines):
- Pre-flight scan — Before writing any code, list all phases with expected file/function counts.
- No abbreviation — Never use "similar to above", "same pattern", "etc.", or "// ..." as placeholders for real code or test bodies. Write every function, test, and config entry in full.
- Equal depth — Later phases must receive the same implementation rigor as Phase 1. If a phase thins out, stop and expand before continuing.
- Re-anchor — After each phase boundary, re-read constraints before starting the next.
- Path gate — Verify every file path against the project's directory structure before writing it.
- Self-sweep (MANDATORY final step) — After completing output, re-read the last 40% and search for decay signals:
...,same pattern,as above,etc.,{ ... },// similar tests,and N more,repeat for. Expand every match in-place. Do not deliver code containing unexpanded shortcuts.Full methodology:
large-task-fidelity.instructions.md
Mode Detection — Resolve Before Any Protocol
How you were invoked determines what you do — check this first:
- Pipeline mode — Your opening prompt says "The pipeline is routing to you" or explicitly references
pipeline-state.json. → Follow the Accepting Handoffs protocol below. Read state, satisfy gates, and callnotify_orchestratorwhen done. - Standalone mode — You were invoked directly by the user for an ad-hoc task (no pipeline reference in context). → Do NOT read
pipeline-state.json. Do NOT callnotify_orchestratororsatisfy_gate. Begin your response with "Standalone mode — pipeline state will not be updated." Then perform the requested work using your expertise,project-config.md, and the skills/instructions below.
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.
- 21d ago Changed 554305f1d683
- 1mo ago Changed cedce999f487
- 1mo ago First seen · 1,262 lines · 25 tokens per session scan A c67db1ed3320
Implement is an agent published in the GitHub repository saajunaid/caddis-plugin (0 stars, last pushed yesterday), licensed MIT. It adds 25 tokens to every session and 12,991 once invoked, about $0.0001 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 2026-08-31.
Other agents, from other repositories
executor
A coding agent that implements requirements and makes tests pass using TDD, a method of writing tests before the implementation, or DDD, a way to structure code around business concepts.
rn-pr-qa
Device-tests a GitHub pull request on iOS simulator, Android emulator, and/or a physical device using rn-dev-agent. Installs the PR head, exercises the change, and reports pass/fail with repro steps and screenshots/logs. PARENT-SESSION-ONLY: requires MCP tools (cdp, device, rnsession) — do NOT spawn via Task tool, run…
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.