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.
npx agentmods add commands/hundia/autospec/plan-sprintgit clone --depth 1 https://github.com/Hundia/autospecWrote 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/commands/hundia/autospec/plan-sprint)<a href="https://agentmods.dev/commands/hundia/autospec/plan-sprint"><img src="https://agentmods.dev/badge/commands/hundia/autospec/plan-sprint.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 | $0.00000 | $0.02746 |
| Opus 5 | $0.00000 | $0.01373 |
| Sonnet 5 | $0.00000 | $0.00549 |
| Haiku 4.5 | $0.00000 | $0.00275 |
Grade A, and why
plan-sprint 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.
How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Sprint
Assemble a team of expert AI agents to collaboratively plan a sprint before building it. Experts analyze the goal in parallel, then three PMs (drafter → reviewer → finalizer) produce a production-ready sprint plan for the backlog.
Usage
/plan-sprint [goal description]
Examples:
/plan-sprint Add user authentication with JWT and social login/plan-sprint Refactor payment processing to support subscriptions/plan-sprint Build admin dashboard with analytics and user management
Instructions
When this command is invoked, execute the 6-phase planning workflow below. The argument $ARGUMENTS is the sprint goal description.
Phase 1: Goal Analysis & Expert Selection
-
Validate the goal. If
$ARGUMENTSis empty or too vague (fewer than 5 words, no clear deliverable), ask the user to clarify:I need a clearer sprint goal. Please describe: - What feature/fix/improvement you want - Who it's for (which user personas) - Any specific subsystems involved Example: "Add user authentication with JWT, social login, and role-based access control" -
Read
specs/backlog.md— scan all## Sprint Xheaders to determine the next sprint number. -
Read
docs/index — identify which subsystems the goal touches. Cross-reference with existing documentation sections. -
Determine which experts to activate based on the goal:
Expert Role Activate When Reads Architect System design, API contracts, integration ALWAYS specs/02_backend_lead.md,specs/03_frontend_lead.md, project entry points, relevantdocs/UX/UI Expert User flows, components, accessibility Sprint has ANY frontend/GUI work specs/10_ui_designer.md,docs/ui-design-system/,docs/flows/Database Expert Schema changes, migrations, query patterns Sprint has schema changes or new models specs/04_db_architect.md,docs/architecture/database.md, schema fileHuman Experience Expert User journeys, personas, cognitive load Sprint has user-facing features specs/01_product_manager.md, relevantdocs/flows/for affected user journeys
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.
- 4d ago First seen · 302 lines · 0 tokens per session scan A 849d536d39de
plan-sprint is a command published in the GitHub repository Hundia/autospec (4 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,746 tokens. 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 commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.