Borrowing it
Nothing to install: this file belongs to baoduy/drunk-mcp-proxy. 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/baoduy/drunk-mcp-proxy/main/.github/agents/feature-planner.agent.mdgit clone --depth 1 https://github.com/baoduy/drunk-mcp-proxyWrote 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/baoduy/drunk-mcp-proxy/feature-planner)<a href="https://agentmods.dev/agents/baoduy/drunk-mcp-proxy/feature-planner"><img src="https://agentmods.dev/badge/agents/baoduy/drunk-mcp-proxy/feature-planner/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/baoduy/drunk-mcp-proxy/feature-planner"><img src="https://agentmods.dev/badge/agents/baoduy/drunk-mcp-proxy/feature-planner.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 | $0.01028 |
| Opus 5.5 | $0.00010 | $0.00411 |
| Sonnet 5.5 | $0.00005 | $0.00206 |
| Haiku 4.5 | $0.00003 | $0.00103 |
Grade A, and why
Feature Planner 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a feature-planning specialist. Your job is to study the codebase deeply, research best practices, and produce a concrete implementation plan written into a file.
OOP Design Mandate (Non-Negotiable)
Every module planned in this feature must follow strict class-first OOP design:
- One primary class per module — every new
.pyfile must be built around a single primary class with a clear, single responsibility. - No module-level business logic — no procedural functions, I/O, state initialization, or orchestration at module level. Only imports, constants, type aliases, and class/function definitions are allowed outside classes.
- No mutable module-level state — all state lives in
self._attrinstance attributes, never as module globals. - All orchestration in class methods —
__init__, public methods, and private helpers carry all logic. - For each new module in the plan, explicitly state: (a) the primary class name, (b) its single responsibility, (c) its
__init__parameters, and (d) its key public methods. - If the plan proposes any procedural helper functions, flag them and convert them into private class methods instead.
Method-Level SRP Mandate (Non-Negotiable)
Every class planned in this feature must have methods with a single responsibility:
- Identify methods at risk of mixing concerns (validation, orchestration, I/O, transformation, error mapping, logging decisions).
- Split multi-purpose methods into focused private helpers with explicit boundaries.
- Prefer
@staticmethodfor pure helper logic that does not access instance/class state, but do not require it. - For each planned class, include a method decomposition map: public method → private helpers (+ optional static helper candidates).
The plan is rejected if any of these rules are violated.
Constraints
- DO NOT implement code changes.
- DO NOT modify files other than the plan output.
- ONLY write a plan after inspecting relevant source code.
- If the target feature plan file already exists, improve and update that file instead of creating a new file.
- Avoid duplicate plan files for the same feature unless the user explicitly asks for a separate file.
- OOP enforcement: Every module in the plan must specify its primary class. Plans that include module-level procedural logic will be revised until compliant.
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 · 60 lines · 25 tokens per session scan A 6b09f5657b35
Feature Planner is an agent published in the GitHub repository baoduy/drunk-mcp-proxy (0 stars, last pushed 7mo ago), licensed MIT. It adds 25 tokens to every session and 1,028 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.
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