conducty-plan

conducty-plan is a skill for Claude Code, Codex from robertbarclayy/conducty. It costs 85 tokens per session (2,444 once invoked), scanned A, original, MIT.

A batch-planning method that turns a request into timed prompts arranged in parallel groups. It also loads earlier notes and recurring problem patterns before planning.

In plain words
What is it for?
It helps create execution plans with prompts, success checks, progress markers, and review levels.
Why use it?
It avoids planning each prompt in isolation and makes the work easier to divide, track, and review.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; mentions Claude Code.

Good fit It helps create execution plans with prompts, success checks, progress markers, and review levels.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/robertbarclayy/conducty/conducty-plan
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 robertbarclayy/conducty --skill conducty-plan
Clone the repo
git clone --depth 1 https://github.com/robertbarclayy/conducty

Made for: Claude Code, Codex.

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 conducty-plan

README.md
[![agentmods](https://agentmods.dev/badge/skills/robertbarclayy/conducty/conducty-plan/github.svg)](https://agentmods.dev/skills/robertbarclayy/conducty/conducty-plan)
Your own site
<a href="https://agentmods.dev/skills/robertbarclayy/conducty/conducty-plan"><img src="https://agentmods.dev/badge/skills/robertbarclayy/conducty/conducty-plan/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 conducty-plan

Your own site · 80×15
<a href="https://agentmods.dev/skills/robertbarclayy/conducty/conducty-plan"><img src="https://agentmods.dev/badge/skills/robertbarclayy/conducty/conducty-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,444 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 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.
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 $0.00085 $0.02444
Opus 5 $0.00043 $0.01222
Sonnet 5 $0.00017 $0.00489
Haiku 4.5 $0.00009 $0.00244

Measured 9d ago against content hash c1d6a6bf5936, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

conducty-plan 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 9d 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.

skills/conducty-plan/SKILL.md · 214 lines

How it starts

The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Conducty Plan — Batch Planning

Generate a structured plan of time-budgeted prompts organized into parallel groups with tracer markers, calibrated review levels, and prompt quality checks.

A plan is a unit of work, not a calendar boundary. Run a fresh plan whenever you start a new orchestration cycle — multiple plans per day are normal. Each plan note is named Plans/Plan YYYY-MM-DD HHmm [Topic].md and lives in the Obsidian vault.

[!important] Read [[conducty-obsidian]] first Vault location, naming, frontmatter, indexes, and link conventions are defined there. Every read/write below assumes those conventions.

Workflow

Step 1: Load the Past From the Vault

Read these from the vault (resolve $CONDUCTY_VAULT, default ~/Obsidian/Conducty/):

  • Latest plan: Glob Plans/Plan *.md, sort by date then time frontmatter, pick the newest. Inspect:
    • Carry-forward items (status: needs-fix, partial, blocked)
    • Hill chart positions
    • End-of-plan summary
  • Latest improvement: Glob Improvements/Improvement *.md, pick newest — what experiments to apply now
  • [[Failure Patterns]] — recurring patterns to avoid
  • [[Metrics]] — last 7-14 rows for trend data (pass rate, retries, appetite accuracy)

If the vault is empty, note it's a fresh start and proceed.

Step 2: Load Context

Read all context hub notes in the vault (use Glob Context/**/Context *.md). Each is a project summary from [[conducty-context]] with bounded contexts, recent changes, characterization data.

If no context notes exist, ask which projects the user is working on and offer to run [[conducty-context]].

Step 3: Gather Goals and Set Appetite

Ask the user what they want to accomplish, then ask for the plan's appetite:

"What are your goals for this plan? And how much time should it consume — an hour? Half a day? Full day?"

The appetite constrains the total plan. If goals exceed appetite, cut scope — don't overcommit. This is the most important planning decision.

Read the full file on GitHub · 214 lines

Files

What ships with it

9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 9d ago First seen · 214 lines · 85 tokens per session scan A c1d6a6bf5936

Subscribe to this mod's changes

conducty-plan is a skill published in the GitHub repository robertbarclayy/conducty (176 stars, last pushed 2mo ago), licensed MIT. It adds 85 tokens to every session and 2,444 once invoked, about $0.0004 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.

Related

Other skills, from other repositories

llm-app-patterns

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

davila7/claude-code-templates · 54 tokens

prompt-optimization

Improve a prompt on the evaluations workbench through a measured loop. Score the baseline first, then duplicate the target column, form a hypothesis from failing rows, edit the copy's prompt draft, run, compare pass rate and cost, and repeat until the numbers hold. Use when the user asks to optimize or improve a…

langwatch/langwatch · 105 tokens

enhance-prompt

Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.

google-labs-code/stitch-skills · 41 tokens

prompt-engineer

Writes, refactors, and evaluates prompts for LLMs — generating optimized prompt templates, structured output schemas, evaluation rubrics, and test suites. Use when designing prompts for new LLM applications, refactoring existing prompts for better accuracy or token efficiency, implementing chain-of-thought or few-shot…

Jeffallan/claude-skills · 93 tokens

seedance-vocab-en

This skill should be used when an English Seedance 2.0 prompt needs clearer production wording, less generic prose, or precise vocabulary for camera, lighting, motion, VFX, audio, and constraints. Route blocked prompts through seedance-filter for context and boundary review.

Emily2040/seedance-2.0 · 61 tokens

ideogram4

Prompting patterns for Ideogram 4 text-to-image — best-in-class in-image text rendering and exact color/layout control via structured JSON captions. Use when generating images that need legible on-image text (title cards, thumbnails, logos, signage, CTAs), precise brand colors, or controlled spatial layout. Triggers…

digitalsamba/claude-code-video-toolkit · 99 tokens