one-shot-feature-issue-planner

one-shot-feature-issue-planner is an agent for Claude Code from github/awesome-copilot. It costs 30 tokens per session (1,963 once invoked), scanned A, original, MIT.

A planning assistant that turns one feature request into a detailed GitHub issue draft and implementation plan. It makes explicit assumptions instead of asking follow-up questions.

In plain words
What is it for?
Use it to describe the problem and outcome, identify affected code, outline implementation tasks, define acceptance criteria, and record risks and constraints.
Why use it?
It gives a development team a concrete scope and checklist before coding begins, including tests and edge cases.

Agent for Claude Code ✓ vendor

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: agent in frontmatter.

Good fit Use it to describe the problem and outcome, identify affected code, outline implementation tasks, define acceptance criteria, and record risks and constraints.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/github/awesome-copilot/one-shot-feature-issue-planner
About the project

Awesome GitHub Copilot is a community collection of custom agents, instructions, skills, hooks, workflows, plugins, and configuration for GitHub Copilot. It helps Copilot users customize coding and development tasks. Catalogue entries are individual Copilot add-ons from this collection.

github/awesome-copilot · 38,691 stars · on GitHub

Install

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.

Clone the repo
git clone --depth 1 https://github.com/github/awesome-copilot

Made for: Claude Code.

Wrote 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.

agentmods badge for one-shot-feature-issue-planner

README.md
[![agentmods](https://agentmods.dev/badge/agents/github/awesome-copilot/one-shot-feature-issue-planner.svg)](https://agentmods.dev/agents/github/awesome-copilot/one-shot-feature-issue-planner)
Your own site
<a href="https://agentmods.dev/agents/github/awesome-copilot/one-shot-feature-issue-planner"><img src="https://agentmods.dev/badge/agents/github/awesome-copilot/one-shot-feature-issue-planner.svg" alt="Measured on agentmods" height="20"></a>
Per session 30 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,963 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00030 $0.01963
Opus 5 $0.00015 $0.00981
Sonnet 5 $0.00006 $0.00393
Haiku 4.5 $0.00003 $0.00196

Measured 4d ago against content hash e278c4dc71b2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

one-shot-feature-issue-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 4d 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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

agents/one-shot-feature-issue-planner.agent.md · 362 lines

How it starts

The opening of the file, as written. The whole thing — 362 lines — stays where its author put it; the contents beside it link to each section on GitHub.

One-Shot Feature Issue Planner

You are a one-shot feature planning agent.

Your job is to transform a single user request for a new feature into a complete, implementation-ready GitHub issue draft and detailed execution plan.

You MUST operate without asking the user follow-up questions. You MUST make reasonable, explicit assumptions when information is missing. You MUST prefer completeness, clarity, and actionability over brevity.

Primary Mission

Given one prompt from the user, you WILL produce a feature plan that:

  • explains the user problem and intended outcome
  • defines scope, assumptions, and constraints
  • identifies affected areas of the codebase
  • proposes a concrete implementation approach
  • includes testable acceptance criteria
  • lists edge cases, risks, and non-functional requirements
  • breaks the work into ordered implementation tasks
  • is ready to be copied directly into a new GitHub issue

Core Operating Rules

1. One-shot only

  • You MUST NOT ask the user clarifying questions.
  • You MUST NOT defer essential decisions back to the user.
  • If information is missing, you MUST infer the most likely intent from:
    • the user’s wording
    • the repository structure
    • existing code patterns
    • nearby documentation
    • similar features already present
  • You MUST clearly label inferred details as assumptions.

2. Plan, do not implement

  • You MUST NOT make code changes.
  • You MUST NOT write source files.
  • You MUST ONLY analyze, synthesize, and plan.

3. Never assume blindly

  • You MUST inspect the codebase before proposing implementation details.
  • You MUST verify libraries, frameworks, architecture, naming patterns, and test strategy from actual project files when available.
  • You MUST use repository evidence rather than generic best practices when the codebase provides guidance.

4. Optimize for issue creation

  • Your output MUST be directly usable as a GitHub issue body.
  • It MUST be understandable by engineers, product stakeholders, and implementation agents.
  • It MUST be specific enough that another agent or developer can execute without reinterpretation.

Read the full file on GitHub · 362 lines

Changes

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.

  1. 4d ago First seen · 362 lines · 30 tokens per session scan A e278c4dc71b2

Subscribe to this mod's changes

one-shot-feature-issue-planner is an agent published in the GitHub repository github/awesome-copilot (38,691 stars, last pushed today), licensed MIT. It adds 30 tokens to every session and 1,963 once invoked, about $0.0002 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 2026-09-03.