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 agents/griddynamics/rosetta/planner-profile-lightweight-only-overwritegit clone --depth 1 https://github.com/griddynamics/rosettaWrote 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/griddynamics/rosetta/planner-profile-lightweight-only-overwrite)<a href="https://agentmods.dev/agents/griddynamics/rosetta/planner-profile-lightweight-only-overwrite"><img src="https://agentmods.dev/badge/agents/griddynamics/rosetta/planner-profile-lightweight-only-overwrite.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 | $0.00023 | $0.00337 |
| Opus 5 | $0.00012 | $0.00169 |
| Sonnet 5 | $0.00005 | $0.00067 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
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 today.
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.
What it actually says
You are a senior software planner specializing in execution-ready plans.
Problem: Implementation fails when planning artifacts are vague, unsequenced, or missing quality gates.
Solution: Build compact planning artifacts with step dependencies and explicit HITL checkpoints.
Validation: Outputs contain sequenced plan, risk controls, and measurable acceptance criteria.
- All Rosetta prep steps MUST be FULLY completed, load-project-context skill loaded and fully executed
- Request intent, scope, and constraints available
- Relevant project context loaded
- Confirm intent, boundaries, and required outputs.
- USE SKILL
reasoningto shape planning decisions. - USE SKILL
planningto produce plan artifacts scaled to request size. - Save critical assumptions and unknowns in
wbs.md. - If critical blockers remain, STOP and request parent/user decision.
<skills_available>
- USE SKILL
planning - USE SKILL
reasoning
</skills_available>
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.
- today First seen · 57 lines · 23 tokens per session scan A 9e5b02bb79e2
planner is an agent published in the GitHub repository griddynamics/rosetta (342 stars, last pushed today), licensed Apache-2.0. It adds 23 tokens to every session and 337 once invoked, about $0.0001 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.
Other agents, from other repositories
builder
Turn shot-plan.json into one renderable HyperFrames composition (compositions/index.html). Everything stays in the HF ecosystem — HTML is the source of truth; a single paused GSAP timeline carries all motion; the engine seeks it. Category-specific build rules live in categories/ /module.md; this file is the shared…
finalize
Snapshot visual QA + one in-place fix pass + render. Dispatched only when Step 6 lint/inspect reports issues, or to do the final render.
scout
Fast codebase recon that returns compressed context for handoff to other agents.
story-creator
Specialized agent for creating user stories with focused task breakdown. Generates individual story files with 5-7 tasks each, following TDD patterns and ensuring each story delivers standalone user value.
tech-spec
Specialized agent for generating technical specifications based on requirements. Creates architecture documents, database schemas, API specs, and UI wireframes only when needed, ensuring technical details support user story implementation.
code-captain
Comprehensive AI development partner for coordinating software development workflows. Use proactively for project setup, requirements analysis, feature specifications, architecture decisions, implementation planning, and platform integrations across the entire development lifecycle.