Agent skill

Conducty Plan

by robertbarclayy in robertbarclayy/conducty

Batch planning of AI prompts. An agent skill from robertbarclayy/conducty.

MITAuto-check passed

Install Conducty Plan

skills CLI
$ npx skills add robertbarclayy/conducty --skill conducty-plan -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install robertbarclayy/conducty conducty-plan --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/robertbarclayy/conducty.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/conducty-plan .claude/skills/conducty-plan && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
conducty-plan
GitHub stars
176
Token cost
~2.6k tokens
SKILL.md length
1,342 words
Files
10
Skills in repo
20
Repo updated
First seen
Licence
MIT

At a glance

Batch planning of AI prompts. An agent skill from robertbarclayy/conducty.

  • Works in 10 steps: Load the Past From the Vault → Load Context → Gather Goals and Set Appetite → …
  • The user says plan
  • SKILL.md covers Workflow and Guidelines
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Conducty Plan is an agent skill from robertbarclayy/conducty. Batch planning of AI prompts. Loads vault context (latest plan, latest improvement, project context, failure patterns, metrics), sets appetite, generates time-budgeted prompts with tracer markers and calibrated review levels. Use when the user says "plan", "plan this work", "batch plan", "create a plan", or wants to organize prompts. Multiple plans per day are expected — each plan is timestamped.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files (for example `plan-template.md`, `prompt-templates/bugfix.md` and `prompt-templates/decision.md`).

It works with Obsidian. The repository describes itself as: Stop context-switching. Start batch-planning. Conducty replaces the fragmented cycle of plan → prompt → wait → get distracted → review → fix → repeat with advanced batch planning. The licence is MIT.

When your agent uses it

  • The user says plan
  • Wants to organize prompts

Example prompts

  • “plan this work”
  • “batch plan”
  • “create a plan”
  • “/conducty-plan”

Workflow steps

10 steps, taken from the step headings in SKILL.md.

  1. Load the Past From the Vault
  2. Load Context
  3. Gather Goals and Set Appetite
  4. Shape Gate — Design Non-Trivial Goals
  5. Generate the Plan
  6. Group for Parallelization
  7. Hill Chart Positions
  8. Wire Wikilinks
  9. Present and Refine
  10. Execution Handoff

What it can do on your machine

Read from SKILL.md and the folder at commit 64aefd5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Conducty Plan loads about 2.6k tokens when it runs. Until then it costs about 103 tokens; SKILL.md has 1,342 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~103
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from robertbarclayy/conducty at commit 64aefd5, republished under its MIT licence (© robertbarclayy). 1,342 words, ~2,630 tokens.

Download SKILL.mdSave it as .claude/skills/conducty-plan/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
conducty-plan
description
Batch planning of AI prompts. Loads vault context (latest plan, latest improvement, project context, failure patterns, metrics), sets appetite, generates time-budgeted prompts with tracer markers and calibrated review levels. Use when the user says "plan", "plan this work", "batch plan", "create a plan", or wants to organize prompts. Multiple plans per day are expected — each plan is timestamped.
aliases
conducty-plan, plan
tags
conducty/skill, conducty/plan

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.

Accept freeform input. Reference carried-forward items from the prior plan.

Step 4: Shape Gate — Design Non-Trivial Goals

For each goal, estimate complexity:

  • Low: Clear requirements, 1-2 files, obvious implementation
  • Medium: Some design decisions, 3-5 files, acceptance criteria need defining
  • High: Multiple subsystems, architectural decisions, unclear requirements

Medium and High goals: Invoke [[conducty-shape]] before writing prompts. The shaping skill produces a Design YYYY-MM-DD HHmm {Topic}.md note in the vault with appetite, acceptance criteria, no-go zones, and component breakdown.

Low goals: Proceed directly to Step 5.

The user can skip shaping for a specific goal — note it as (design skipped by user).

Step 5: Generate the Plan

Resolve current date and time. Pick a topic suffix if more than one plan is expected today (recommended for clarity even when only one plan runs).

Create Plans/Plan YYYY-MM-DD HHmm [Topic].md in the vault. Use the [[plan-template]] (despite the name, the template is per-plan, not per-day).

Frontmatter must include:

yaml
---
type: plan
date: YYYY-MM-DD
time: HHmm
topic: {topic title case}        # optional
appetite: {e.g., 4h}
project: {project-name}          # if scoped to one
tags: [conducty, conducty/plan]
---

Then prepend a wikilink to [[Plans Index]].

5a: Map File Structure Per Goal

Before writing prompts, map which files will be created or modified:

  • Design units with clear boundaries and one responsibility per file
  • Follow established patterns in existing codebases (use Glob/Grep to verify)
  • Identify characterization needs for files that will be modified
5b: Decompose Into Prompts

For each goal, select and fill a prompt template from prompt-templates/:

  • [[feature]] — new feature with acceptance criteria and TDD
  • [[bugfix]] — bug fix with reproduction, root cause hypothesis, regression test
  • [[refactor]] — restructuring with characterization-first approach
  • [[test]] — writing or improving test coverage
  • [[decision]] — architectural decision using [[conducty-dialectic]]
  • [[security]] — auth, input validation, secrets, hardening (full-review always)
  • [[migration]] — schema/version/data migration with expand-contract steps
  • [[performance]] — latency/throughput/memory work, measurement-driven

For each prompt:

  1. Write the full prompt text using the template — be specific with file paths, code, and behavior
  2. Assign a project and directory
  3. Scope the context — only files and directories this prompt needs
  4. Set a time budget — derived from the goal's appetite, divided across its prompts
  5. Add a verification step — a single command with expected output
  6. Estimate complexity (Low / Medium / High)
  7. Assign a review level based on complexity (see below)
  8. Note dependencies — does this prompt depend on another finishing first?
  9. Reference the design note wikilink if one was created in Step 4
  10. Include no-go zones from the design to prevent scope creep
5c: Assign Review Levels (Calibrated Rigor)

Not every prompt needs the same review overhead:

ComplexityReview LevelWhat Happens
Lowverify-onlyRun verification command. If it passes, done.
Mediumspec-reviewRun verification + dispatch spec compliance reviewer.
Highfull-reviewRun verification + spec compliance + code quality review.

This is more efficient than blanket two-stage review for everything. Reserve ceremony for work that warrants it.

5d: Mark Tracers

In each parallelization group, mark the first prompt as Tracer: yes. This prompt runs alone before the rest of the group. If it fails, the plan's assumptions for that group need revision — don't blindly execute the remaining prompts.

Choose the tracer wisely: pick the prompt most likely to expose bad assumptions (touches the most shared code, tests the most uncertain part of the design, or integrates with the least-understood system).

Show full SKILL.md (534 more words)Show less
5e: Prompt Quality Gate

Before finalizing, check each prompt for prompt smells (signs it will fail):

SmellSymptomFix
Vague acceptance"Make it work" / "Improve performance"Add concrete criteria with numbers
Missing contextReferences files not listed in Context fieldAdd the missing file paths
Mixed concernsOne prompt does two unrelated thingsSplit into two prompts
No verificationNo command to prove successAdd a test command with expected output
Unbounded scopeNo no-go zones, open-ended "and anything else"Add explicit boundaries
Exceeds appetiteTime budget > what's reasonable for complexitySimplify or split
Missing characterizationModifies existing code without verifying current behaviorAdd characterization step

Any prompt with a smell gets fixed before the plan is finalized. A smelly prompt is a wasted execution slot.

Step 6: Group for Parallelization

Organize prompts into groups:

  • Group A: Independent prompts that can all run in parallel
  • Group B: Prompts that depend on Group A completing
  • Group C: And so on

Within each group, all prompts are independent. The first prompt in each group is the tracer.

Step 7: Hill Chart Positions

For each goal, mark its starting hill position:

  • Uphill (figuring it out) — goal still has open design questions or uncertainty
  • Peak — design is solid, execution is the remaining work
  • Downhill (making it happen) — clear path, just needs implementation

Goals that are uphill after shaping may need more design work. Goals that are downhill should execute smoothly — if they don't, the design missed something.

In the plan note's ## Related section, link:

  • [[Plans Index]]
  • The design notes consumed (e.g. [[Design 2026-04-27 0930 Auth Cleanup]])
  • The context notes loaded (e.g. [[Context My App]])
  • The improvement note whose experiments are being tested (e.g. [[Improvement 2026-04-26 1830]])
  • Any prior plan whose work carries forward
  • Accumulating notes this plan will append to: [[Failure Patterns]], [[Metrics]], [[Prompt Log]]

Then prepend the new plan's wikilink to [[Plans Index]] (Edit, not Write).

Step 9: Present and Refine

Show the user the generated plan. Ask:

  • "Does this fit your appetite?"
  • "Should I adjust any priorities, groupings, or review levels?"
  • "Any prompts to add, remove, or split?"

Iterate until satisfied, then write the final version to the vault.

Step 10: Execution Handoff

After the plan is finalized:

  • [[conducty-execute]] (recommended): Automated subagent execution with tracer-first approach and calibrated review
  • Manual execution: User copies prompts into separate Claude Code sessions
  • Hybrid: Use [[conducty-execute]] for Low/Medium, manual for High

Guidelines

  • Appetite constrains everything — if goals exceed the budget, cut scope, don't overcommit
  • Each prompt is self-contained — enough context to execute without follow-up questions
  • Smaller prompts > fewer large ones — smaller prompts have higher first-attempt success rates
  • Scope context per prompt — only what it needs, not the entire project
  • Every prompt has verification — no exceptions
  • Tracers validate the plan — if a tracer fails, it's a plan problem
  • Review level matches risk — don't waste ceremony on low-risk work
  • No-go zones in every prompt — prevent the most common failure mode (agent scope creep)
  • Learn from the vault — prior failure patterns and improvement experiments visibly shape this plan's prompts
  • Prompt smells get fixed before execution — a smelly prompt is a wasted slot
  • Index discipline — every new plan is prepended to [[Plans Index]] in the same action that creates it

© robertbarclayy, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files in skills/conducty-plan of robertbarclayy/conducty.

  • SKILL.md
  • plan-template.md
  • prompt-templates/bugfix.md
  • prompt-templates/decision.md
  • prompt-templates/feature.md
  • prompt-templates/migration.md
  • prompt-templates/performance.md
  • prompt-templates/refactor.md
  • prompt-templates/security.md
  • prompt-templates/test.md

Open the folder on GitHubat commit 64aefd5

Compare with similar skills

Conducty Plan next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Conducty Plan compared with similar skills
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Conducty Plan this skillrobertbarclayy/conducty176—~2.6kAutomated safety check: PassMIT
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Knap Markdown Templateskepano/obsidian-skills49k2 repos~986Automated safety check: PassMIT
JSON Canvasheyitsnoah/claudesidian2.6k18 repos~3.5kAutomated safety check: PassMIT
Obsidian MarkdownAtmosphere/atmosphere3.8k20 repos~1.3kAutomated safety check: PassApache-2.0
Obsidian CLIAtmosphere/atmosphere3.8k13 repos~795Automated safety check: PassApache-2.0

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Works with

Questions about Conducty Plan

What does Conducty Plan do?

Batch planning of AI prompts. An agent skill from robertbarclayy/conducty. Conducty Plan is an agent skill from robertbarclayy/conducty. Batch planning of AI prompts.

When should I use Conducty Plan?

Conducty Plan fits situations like: the user says plan; wants to organize prompts.

How do I install Conducty Plan in Claude Code?

Run `npx skills add robertbarclayy/conducty --skill conducty-plan -a claude-code`. Or copy the skill folder (skills/conducty-plan in robertbarclayy/conducty) into .claude/skills/conducty-plan in your project. Claude Code loads it when a task matches its description.

How do I install Conducty Plan in Codex?

Run `npx skills add robertbarclayy/conducty --skill conducty-plan -a codex`. Or copy the skill folder (skills/conducty-plan in robertbarclayy/conducty) into .agents/skills/conducty-plan in your project. Codex loads it when a task matches its description.

Can I use Conducty Plan in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add robertbarclayy/conducty --skill conducty-plan -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/conducty-plan, .gemini/skills/conducty-plan, .github/skills/conducty-plan and .opencode/skills/conducty-plan in your project.

What does Conducty Plan need to run?

SKILL.md names no scripts, command-line tools or credentials: Conducty Plan is instructions for the agent only.

Does Conducty Plan access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Conducty Plan safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Conducty Plan use?

Conducty Plan is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Conducty Plan use?

About 2.6k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Conducty Plan?

Skills that share tags, products or a category with Conducty Plan: Obsidian Bases (Atmosphere/atmosphere, 3.8k stars), Knap Markdown Templates (kepano/obsidian-skills, 49k stars), JSON Canvas (heyitsnoah/claudesidian, 2.6k stars) and Obsidian Markdown (Atmosphere/atmosphere, 3.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Conducty Plan?

robertbarclayy (a GitHub user) maintains it in robertbarclayy/conducty, which has 176 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on June 19, 2026.

Source: robertbarclayy/conducty on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.