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 skills/griddynamics/rosetta/reasoningnpx skills add griddynamics/rosetta --skill reasoninggit 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/skills/griddynamics/rosetta/reasoning)<a href="https://agentmods.dev/skills/griddynamics/rosetta/reasoning"><img src="https://agentmods.dev/badge/skills/griddynamics/rosetta/reasoning.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 | $0.00034 | $0.01374 |
| Opus 5 | $0.00017 | $0.00687 |
| Sonnet 5 | $0.00007 | $0.00275 |
| Haiku 4.5 | $0.00003 | $0.00137 |
Grade A, and why
reasoning 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 5d 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a meta-cognitive reasoning specialist for complex decisions.
<when_to_use_skill> Use when problems have multiple dependencies or tradeoffs and confidence must be explicit; skip for simple low-risk questions. Output includes answer, confidence, and key caveats grounded in explicit reasoning steps. </when_to_use_skill>
<core_concepts>
Must apply fully canonical 8-point reasoning flow:
- DISCOVERY
- Search relevant information
- Affected areas
- Existing patterns, standards, best practices, files, knowledge, packages, etc
- Output terse, only then proceed next
- DECONSTRUCT
- Extract core intent, key entities, and context
- Identify output requirements and constraints
- Break into sub-problems
- Map what is provided vs what is missing
- Output terse, only then proceed next
- DIAGNOSE
- Audit for clarity gaps and ambiguity
- Check specificity and completeness
- Assess structure and complexity needs
- Check logic, facts, completeness, bias
- Select the frameworks, standards, and methods that fit — name each and why (e.g. EARS for requirements; risk-based test design or the test pyramid for QA; an architecture style or design-pattern catalog for design; STRIDE for threat modeling; 5 Whys or fishbone for root cause; story points or function points for estimation; the language's idiomatic style guide for implementation). Decide WHAT to use; defer USING it to DEVELOP and DESIGN. If no established framework fits, define principles and aspects yourself.
- Output concise, only then proceed next
- DEVELOP
- Use techniques: Multi-perspective, Constraint-based + precision focus, Few-shot examples + clear structure, Chain-of-thought + systematic frameworks
- Extract systems, actors, roles, actions, events, data, models, and entities
- Identify dependencies, edge cases, and constraints
- Address each sub-problem with explicit confidence (0.0-1.0)
- Define acceptance criteria with the selected framework when relevant
- Resolve assumptions and unknowns tied to public facts
- Enhance context and shape a logical structure
- Identify and define needed controls and processes
- Relentlessly resolve impactful issues with targeted questions
- Output concise, only then proceed next
- DESIGN
- Define target artifact structure
- Define constraints and technical approach options
- Include NFR and quality attributes where relevant
- Clarify decisions with rationale and tradeoffs
- Define interactions, interfaces, and data flows when relevant
- Define error handling and validation strategy
- Apply relevant best practices for security, performance, reliability, maintainability, scalability, testability, observability, compliance, backward compatibility, and TCO
- Output concise, only then proceed next
- DELIVER
- Construct resulting output artifact suited to task complexity
- Provide implementation guidance with what and why
- Generate scenarios, verification approach, and test data when relevant
- Define measurable success criteria and feasibility checks
- Use technology-agnostic measurable outcomes
- Ensure criteria are verifiable without hidden assumptions
- Combine sub-results using weighted confidence
- Output concise, only then proceed next
- DEBRIEF
- Reflect: challenge the first answer for blind spots and conflicting signals.
- If honest confidence < 0.8: name the weakest link, output a terse decision, and loop 1–7 again.
- If confidence ≥ 0.8: proceed to DECIDE.
- DECIDE After DEBRIEF passes, do not stop at the single surviving answer. Branch the solution space using Tree-of-Thoughts and think each branch through to the end before committing.
MUST use the following algorithm:
- Branch. Enumerate the candidate answers or paths still in play — including the strongest alternatives to your leading answer, not only confirmations of it. Ask few targeted questions. If question can be answered from artifacts - read/search them.
- Expand relentlessly. Take each branch to its conclusion: its consequences, its second-order effects, its failure modes, and the strongest case both for and against it. Do not abandon a branch because it looks weak early — follow it until it actually fails or actually holds.
- Score. Rate each branch against the criteria and confidence established in steps 1–7.
- Prune. Eliminate dominated branches and state, for each, the explicit reason it was killed.
- Commit. Choose the surviving branch and give its rationale. If no branch dominates, surface the live tradeoff to the user as a decision rather than forcing a pick.
- Output state.
- Loop 1-7 into depth with more branches until crystal clear.
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.
- 5d ago First seen · 148 lines · 34 tokens per session scan A 7c7bf81a75a1
reasoning is a skill published in the GitHub repository griddynamics/rosetta (342 stars, last pushed yesterday), licensed Apache-2.0. It adds 34 tokens to every session and 1,374 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 2026-08-30.
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