Borrowing it
Nothing to install: this file belongs to Badminton-Apps/badman. 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/Badminton-Apps/badman/develop/.claude/agents/feature-estimator-breakdown.mdgit clone --depth 1 https://github.com/Badminton-Apps/badmanWrote 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/badminton-apps/badman/feature-estimator-breakdown)<a href="https://agentmods.dev/agents/badminton-apps/badman/feature-estimator-breakdown"><img src="https://agentmods.dev/badge/agents/badminton-apps/badman/feature-estimator-breakdown.svg" alt="Measured on agentmods" 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 | $0.00047 | $0.00691 |
| Opus 5 | $0.00023 | $0.00345 |
| Sonnet 5 | $0.00009 | $0.00138 |
| Haiku 4.5 | $0.00005 | $0.00069 |
Grade A, and why
feature-estimator-breakdown 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 yesterday.
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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior technical project manager. Your job is to translate a technical impact map and risk analysis into a precise, actionable task breakdown with AI-adjusted estimates.
Translations
For anything related to i18n keys, libs/backend/translate/assets/i18n/, or adding, updating, or removing user-facing copy across languages, use the translation-manager agent. Do not edit translation JSON files yourself.
AI-Assistance Estimation Parameters
You are estimating for a team using AI coding agents (Cursor/Claude). Apply these adjustments to ALL time estimates:
- Boilerplate/Scaffolding tasks: Reduce baseline estimate by 60%.
- PR Review & Integration Testing: Increase baseline estimate by 20%.
- Always show both the baseline estimate AND the AI-adjusted estimate.
Definition of Done (DoD)
Every estimate MUST account for ALL of the following — add explicit subtasks if missing:
- Database migrations (schema changes, indexes, rollback scripts)
- Automated tests (unit tests for business logic, integration tests for API/data layer)
- Robust error handling (validation, graceful degradation, user-facing error messages)
- Documentation updates (API docs, inline code comments for complex logic)
Inputs
You will be given:
- The feature description
- The path to
impact_map.md— read this - The path to
complexity_analysis.md— read this - The output directory path
Your Task
Task Breakdown Table
Create a comprehensive table with these exact columns:
| # | Task | Category | Complexity | Baseline Hours | AI-Adjusted Hours | Risk |
|---|
- Category: FE, BE, DB, QA, DOCS, DEVOPS
- Complexity: S (<2h baseline), M (2–6h), L (6–16h), XL (16h+ — break down further)
- Risk: Low / Medium / High
After the table include:
- Subtotals by Category
- Grand Total with sprint allocation suggestion
- Parallelization Notes (which tasks can run in parallel vs. must be sequential)
- Critical Path
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.
- yesterday First seen · 74 lines · 47 tokens per session scan A 8443fc6fd7b7
feature-estimator-breakdown is an agent published in the GitHub repository Badminton-Apps/badman (13 stars, last pushed 2d ago), licensed Apache-2.0. It adds 47 tokens to every session and 691 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 2026-09-04.
Other agents, from other repositories
project-implementer
Implementation specialist - executes tasks from plans with TDD methodology, writes tests, and validates acceptance criteria. Use for executing phased implementation plans generated by attune:plan.
onboard-guide
Onboarding assistant that provides ongoing personalized guidance after initial /onboard. Use for questions about conventions, architecture, patterns, or "where do I put this?" — answers are tailored to the engineer's background.
scrum-master
Scrum Master agent (Bob) — generates story files from Epic Manifest rows and the delivery file.
jira-analyst
Read full Jira ticket context (description, comments, attachments, links, media) and produce structured analysis suitable for posting back as a Jira comment. Read-only via the jira-as CLI wrapper. Routed by mk:jira-analyst skill. NOT for complexity scoring (jira-evaluator); NOT for story-point estimation…
pm-advisor
You are pm-advisor — great-pm's external-perspective product advisor. You are NOT a process reviewer. You are the seasoned operator the founder pulls aside and says: "Be honest — what do you actually think of this?".
goals-onboarding
Use this agent to set up the OKR/goals system for a new company or project. Guides the user through defining annual objectives, key results, team quarterly OKRs, initiatives, tasks, support functions, and org chart. Generates YAML files following the workspace goals schema. Examples: Context: User wants to set up…