coding-flow

coding-flow is a command for coding agents from griddynamics/rosetta. It costs 24 tokens per session (2,236 once invoked), scanned A, original, Apache-2.0.

Light coding workflow: features, fixes, refactors, unit tests, etc.; scales small to large.

Command

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.

agentmods
npx agentmods add commands/griddynamics/rosetta/coding-flow
Clone the repo
git clone --depth 1 https://github.com/griddynamics/rosetta

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 coding-flow

README.md
[![agentmods](https://agentmods.dev/badge/commands/griddynamics/rosetta/coding-flow.svg)](https://agentmods.dev/commands/griddynamics/rosetta/coding-flow)
Your own site
<a href="https://agentmods.dev/commands/griddynamics/rosetta/coding-flow"><img src="https://agentmods.dev/badge/commands/griddynamics/rosetta/coding-flow.svg" alt="Measured on agentmods" height="20"></a>
Per session 24 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,236 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00024 $0.02236
Opus 5 $0.00012 $0.01118
Sonnet 5 $0.00005 $0.00447
Haiku 4.5 $0.00002 $0.00224

Measured today against content hash 0854a90cd676, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

coding-flow 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.

plugins/core-copilot-light/commands/coding-flow.md · 144 lines

How it starts

The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.

<coding_flow>

<description_and_purpose>

Problem: Unstructured coding leads to scope drift, missing validation, autonomous runaway, and misaligned deliverables. Solution: Sequential workflow with reviewer gates, HITL gates, subagent delegation, and skill-driven execution scaled per Request size classification. Validation: Each phase produces verifiable outputs; reviewer catches issues before user; HITL gates prevent autonomous runaway; final validation confirms implementation matches approved intent. Lightweight variant: a single architect pass produces discovery, design, specs, and plan; one reviewer gate and one HITL gate approve all of it before implementation.

</description_and_purpose>

<workflow_phases>

  1. All Rosetta prep steps MUST be FULLY completed
  2. MUST USE SKILL load-project-context (required: all), orchestration (all except trivial), hitl (all, unless No HITL or Fully Autonomous)
  3. MUST ALWAYS use todo tasks ledger, ASAP. Phases are sequential. Independent tasks can run in parallel.
  4. No rush, take your time, MUST FOLLOW WORKFLOW ENTIRELY, no skipping, if in doubt - select the safest / longest path, no deviation from the workflow is allowed
  5. When debugging is needed, INVOKE SUBAGENT engineer with debugging skill to save LLM context
  6. INVOKE SUBAGENT executor for building, running tests, installing packages, and similar mechanical actions.
  7. MUST just-in-time load each phase's skills
  8. If workflow is for REQUIREMENTS, MUST USE SKILL requirements-use and LOAD all affected requirements. Use refs to requirements for subagents.
  9. If /goal is set repeat phases 4-7 postponing final_validation until goal is met.
  10. If migrate/modernize: implementation phase MUST use tiny batches ONLY (1-3 files), never bulk-read (other phases may); specs/plan enforce; FS-copy RECOMMENDED; no behavior change/new code; mirror source; subagents same; REQUIRED TO log started/completed; Use impl subagents like MAP-REDUCE;
  11. Run architect subagent with required model in the background and consult with it if already supported or prefer advisor if already available
  12. Coding workflow state MUST be saved to agents/TEMP/<FEATURE>/coding-flow-state.md file.
  13. If context already contains request for TDD => implement properly red and green adjusting this workflow, including by moving execution of phases tests and review_tests to be after user_review_design and before implementation.

<solution_design phase="1" applies="ALL" subagent="architect" role="Architect producing discovery, design, specs, and plan in one pass" subagent_required_model="GPT-5.6 Sol, Claude Opus 5, Gemini 3.7 Flash">

Execute strongly in the specified order. A step MUST NOT start before the previous step is complete.

  1. Step 1: Discover project context, affected and related code, dependencies, constraints, and requirements; derive the architecture requirements that address the user request fully. Input: user request + CONTEXT.md + ARCHITECTURE.md + IMPLEMENTATION.md. Do not stop until 100% clear.
  2. Step 2: Design 3 best architecture solutions on high level with pro/cons analysis.
  3. Step 3: Define the best solution, but concise, phrase-terse, compressed, etc. Record Steps 1-3 as concise architecture-notes.md in FEATURE PLAN folder.
  4. Step 4: Once done, USE SKILL tech-specs (load JIT) to create plans/<FEATURE>/<FEATURE>-SPECS.md. Specs own WHAT.
  5. Step 5: Once done, USE SKILL planning (load JIT) to create plans/<FEATURE>/<FEATURE>-PLAN.md. Plan owns HOW. Target: 100% clarity. Cross-reference specs, never duplicate them.
  6. Required skills: reasoning, tech-specs, planning
  7. Recommended skills: questioning, codemap (structural project discovery)
  8. If REQUIREMENTS in use: requirements-use skill is required. Plan/Specs must have pointers to requirements identifiers.
  9. Additionally discover existing libraries, packages, and search web for similar problems/tasks (if this make sense)
  10. SMALL: output specs and plan as message, no files. MEDIUM: concise. LARGE: full.
  11. Update coding-flow-state.md

Read the full file on GitHub · 144 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. today First seen · 144 lines · 24 tokens per session scan A 0854a90cd676

Subscribe to this mod's changes

coding-flow is a command published in the GitHub repository griddynamics/rosetta (342 stars, last pushed today), licensed Apache-2.0. It adds 24 tokens to every session and 2,236 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.