reasoning

reasoning is a skill for Claude Code from griddynamics/rosetta. It costs 34 tokens per session (1,374 once invoked), scanned A, original, Apache-2.0.

A structured method for thinking through complex problems, decisions, and trade-offs, with explicit confidence and caveats.

In plain words
What is it for?
Use it for multi-step decisions, dependency-heavy questions, and problems where the reasoning and limitations need to be clearly stated.
Why use it?
It helps make complicated reasoning easier to follow and exposes missing information or uncertainty before giving an answer.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: model in frontmatter.

Good fit Use it for multi-step decisions, dependency-heavy questions, and problems where the reasoning and limitations need to be clearly stated.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/griddynamics/rosetta/reasoning
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.

Any agent
npx skills add griddynamics/rosetta --skill reasoning
Clone the repo
git clone --depth 1 https://github.com/griddynamics/rosetta

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 reasoning

README.md
[![agentmods](https://agentmods.dev/badge/skills/griddynamics/rosetta/reasoning/github.svg)](https://agentmods.dev/skills/griddynamics/rosetta/reasoning)
Your own site
<a href="https://agentmods.dev/skills/griddynamics/rosetta/reasoning"><img src="https://agentmods.dev/badge/skills/griddynamics/rosetta/reasoning/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for reasoning

Your own site · 80×15
<a href="https://agentmods.dev/skills/griddynamics/rosetta/reasoning"><img src="https://agentmods.dev/badge/skills/griddynamics/rosetta/reasoning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,374 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 8
    Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.
    Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
How audits are shown
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 $0.00034 $0.01374
Opus 5.5 $0.00014 $0.00550
Sonnet 5.5 $0.00007 $0.00275
Haiku 4.5 $0.00003 $0.00137

Measured 1mo ago against content hash 7c7bf81a75a1, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 1mo 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.

instructions/r2/core/skills/reasoning/SKILL.md · 148 lines

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:

  1. DISCOVERY
  • Search relevant information
  • Affected areas
  • Existing patterns, standards, best practices, files, knowledge, packages, etc
  • Output terse, only then proceed next
  1. 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
  1. 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
  1. 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
  1. 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
  1. 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
  1. 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.
  1. 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:

  1. 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.
  2. 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.
  3. Score. Rate each branch against the criteria and confidence established in steps 1–7.
  4. Prune. Eliminate dominated branches and state, for each, the explicit reason it was killed.
  5. 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.
  6. Output state.
  7. Loop 1-7 into depth with more branches until crystal clear.

Read the full file on GitHub · 148 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. 1mo ago First seen · 148 lines · 34 tokens per session scan A 7c7bf81a75a1

Subscribe to this mod's changes

reasoning is a skill published in the GitHub repository griddynamics/rosetta (362 stars, last pushed 2d ago), licensed Apache-2.0. It adds 34 tokens to every session and 1,374 once invoked, about $0.0001 per session on Opus 5.5. 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.