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 skills add griddynamics/rosetta --skill coding-agents-farmgit 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/coding-agents-farm)<a href="https://agentmods.dev/skills/griddynamics/rosetta/coding-agents-farm"><img src="https://agentmods.dev/badge/skills/griddynamics/rosetta/coding-agents-farm/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.
<a href="https://agentmods.dev/skills/griddynamics/rosetta/coding-agents-farm"><img src="https://agentmods.dev/badge/skills/griddynamics/rosetta/coding-agents-farm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 11 findings, up to high
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 →
- high Agent Snooping · line 55 Skill reads from agent configuration directories (.claude/, .codex/, .gemini/). These directories may contain API keys, personal settings, and other credentials that the skill has no legitimate need to access.Fix: Remove all code or instructions that access agent configuration directories (.claude/, .codex/, .gemini/). If configuration values are needed, pass them explicitly as parameters or environment variabl
- high Excessive Agency · line 116 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.
- high Excessive Agency · line 121 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.
- high Excessive Agency · line 131 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.
- 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.
- medium Excessive Agency · line 48 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 55 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 57 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 59 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 139 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 146 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 5.1 | $0.00032 | $0.02549 |
| Opus 5.5 | $0.00013 | $0.01020 |
| Sonnet 5.5 | $0.00006 | $0.00510 |
| Haiku 4.5 | $0.00003 | $0.00255 |
Grade B, and why
coding-agents-farm scanned grade B with 1 finding 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
| `gemini` | `--yolo` (= `-y`) | Env: `GEMINI_YOLO_MODE=true`; Config: `"yolo": true` in `~/.gemini/settings.json`; also `--approval-mode auto_edit` for file-only auto-approve | How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<coding_agents_farm>
<when_to_use_skill> Use when a task benefits from parallel execution across multiple coding agents — large features decomposable into independent subtasks, cross-validation by different models/providers, or throughput-critical work. Solves: single-agent bottlenecks, premature completion without testing, agent deviation, token/rate-limit failures going unnoticed. </when_to_use_skill>
<core_concepts>
MUST EXPLICITLY CONFIRM WITH USER HE WANTS TO DO THAT: IT IS DANGEROUS, IT CAN EAT MONEY VERY QUICK.
USER MUST TYPE EXACTLY Yes, I take responsibility, IF NOT PROVIDED EXACTLY - ASK AGAIN. AFTER 3 FAILED ATTEMPTS: STOP, NO REPLY, REQUEST USER TO START A NEW SESSION. NO OVERRIDE ALLOWED.
Provider-model constraints (enforced, not optional):
| CLI | Provider | Headless cmd | Model flag |
|---|---|---|---|
claude |
Anthropic only | claude -p "PROMPT" |
--model MODEL |
codex |
OpenAI only | codex exec "PROMPT" |
-m MODEL |
copilot |
GitHub-hosted (multi) | copilot -p "PROMPT" |
--model MODEL |
gemini |
Google only | gemini -p "PROMPT" |
-m MODEL |
opencode |
Multi-provider | opencode run "PROMPT" |
-m provider/model |
goose |
Multi-provider (config) | goose run --text "PROMPT" |
Config-based |
Auto-approve flags (use ALL applicable flags, not just one):
| CLI | CLI flags | Env vars / Config (set before launch) |
|---|---|---|
claude |
--dangerously-skip-permissions (= --permission-mode bypassPermissions) |
Settings: "defaultMode": "bypassPermissions" in .claude/settings.json; also "permissions": {"allow": ["Bash","Edit","Write","Read","WebFetch","mcp__*"]} |
codex |
--yolo (= --dangerously-bypass-approvals-and-sandbox, = -a never --sandbox danger-full-access) |
Env: CODEX_UNSAFE_ALLOW_NO_SANDBOX=1 |
copilot |
--yolo (= --allow-all) |
N/A; known issue: may still prompt in some edge cases |
gemini |
--yolo (= -y) |
Env: GEMINI_YOLO_MODE=true; Config: "yolo": true in ~/.gemini/settings.json; also --approval-mode auto_edit for file-only auto-approve |
opencode |
--yolo (= --dangerously-skip-permissions) |
Env: OPENCODE_YOLO=true; Config: "yolo": true in opencode.json; granular: "permission": {"*": {"*": "allow"}} |
goose |
None (config-only) | Config: auto-approve in ~/.config/goose/profiles.yaml |
Known auto-approve issues:
- Claude Code: bug where allowlist permissions silently denied even when configured (as of Feb 2026). Use
bypassPermissionsmode, not allowlists. - Codex:
--yolosuppresses trust prompt but.codex/skillsmay still gate on per-project trust. Fixed in v0.88+. - Copilot:
--yolomay still prompt for some operations in edge cases. No full workaround. - Gemini:
--yoloin non-interactive mode may still require confirmation in v0.28+ (known regression). Set env var as belt-and-suspenders.
YOUR INTERNAL KNOWLEDGE ABOUT MODEL NAMES, CLI FLAGS, AND TOOL VERSIONS IS STALE. Use ONLY the names and flags listed in this skill. Do NOT substitute from memory. If unsure about a model name, omit the model flag and let the CLI use its default.
Model selection guidance:
- Anthropic:
claude-sonnet-5(workhorse),claude-opus-4-8(complex),claude-haiku-4-5(fast) - OpenAI:
gpt-5.4(workhorse),gpt-5.5-high(complex) - Google:
gemini-3.1-pro-preview(workhorse),gemini-3-flash-preview(fast) - Copilot: select via
--model; supports claude, gpt, gemini families through GitHub - OpenCode: prefix with provider, e.g.
anthropic/claude-sonnet-5,openai/gpt-5.4 - Goose: set in
~/.config/goose/profiles.yaml
OpenCode: prefix with provider, e.g. anthropic/claude-sonnet-5, openai/gpt-5.4-medium.
Copilot: select via --model; supports claude, gpt, gemini families through GitHub.
Goose: set in ~/.config/goose/profiles.yaml.
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.
- 1mo ago First seen · 197 lines · 32 tokens per session scan B ee6b744fef54
coding-agents-farm is a skill published in the GitHub repository griddynamics/rosetta (360 stars, last pushed yesterday), licensed Apache-2.0. It adds 32 tokens to every session and 2,549 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
memorix-git-memory
Use when the task depends on commit history, what changed, when a fix shipped, or linking engineering evidence to reasoning memory.
multi-agent-loop
Turn the current repository into a supervised multi-agent coding loop — spawn parallel AI coding agents in isolated git worktrees with file ownership, a shared radar, and human approval gates, then run the loop (status, standup, approvals) from one place.
agent-orchestrator
Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.
gentle-ai-collab-perfect
Trigger: contributing to Gentleman-Programming/gentle-ai as an external collaborator. Strict issue-first workflow, honest PR bodies, contributor-vs-maintainer scope, chained-PR strategy, verification protocol, docstring coverage. Load whenever the active repo is Gentleman-Programming/gentle-ai and any part of the…
branch-pr
Create Gentle AI pull requests with issue-first checks. Trigger: creating, opening, or preparing PRs for review.
work-unit-commits
Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.