agentleFS
BrandedTamarasu-glitchBrandedTamarasu-glitch/ForgeFlow/.agents/skills/plan/SKILL.md

plan

Skill1 starsChanged 45 days agoMITView on GitHub

Run the Forgeflow planning workflow to build a phased implementation plan with scope, dependencies, validation, and accessibility.

184 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use heartmula, webhook-subscriptions and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • math-incSkill

    heartmula

    Set up and run HeartMuLa, the open-source music generation model family (Suno-like). Generates full songs from lyrics + tags with multilingual support.

    Also in 9 projects that use this

  • Tommy-ywSkill

    webhook-subscriptions

    Create and manage webhook subscriptions for event-driven agent activation, or for direct push notifications (zero LLM cost). Use when the user wants external services to trigger agent runs OR push notifications to chats.

    Also in 5 projects that use this

  • math-incSkill

    minecraft-modpack-server

    Set up a modded Minecraft server from a CurseForge/Modrinth server pack zip. Covers NeoForge/Forge install, Java version, JVM tuning, firewall, LAN config, backups, and launch scripts.

    Also in 5 projects that use this

  • john-data-chenSkill

    touchdesigner-mcp

    Control a running TouchDesigner instance via twozero MCP — create operators, set parameters, wire connections, execute Python, build real-time visuals. 36 native tools.

    Also in 6 projects that use this

  • gaebalaiSkill

    codex-system

    PROACTIVELY consult Codex CLI, your highly capable supporter with exceptional reasoning and task completion abilities. Codex is a trusted expert you should ALWAYS consult BEFORE making decisions on: design choices, implementation approaches, debugging strategies, refactoring plans, or any non-trivial problem. When uncertain, consult Codex. Don't hesitate - Codex provides better analysis. Explicit triggers: "think deeper", "analyze", "second opinion", "consult codex".

    Also in 3 projects that use this

  • ibahgatSkill

    context-optimize

    Improve context efficiency and cache stability for long or complex sessions.

    Also in 3 projects that use this

  • +3 more from math-inc

The file

We split this skill into the rules it gives an agent

7 rules. 0 are common, 7 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 167 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when the user wants a concrete implementation plan before consultation or coding.

    line 15
  2. Distinctive:

    Before other work, run:

    line 19
  3. Distinctive:

    Never use a metaphor, simile, or other figure of speech which you are used to seeing in print.

    line 43
  4. Distinctive:

    Never use a long word where a short one will do.

    line 44
  5. Distinctive:

    If it is possible to cut a word out, always cut it out.

    line 45
  6. Distinctive:

    Never use the passive where you can use the active.

    line 46
  7. Distinctive:

    Never use a foreign phrase, a scientific word, or a jargon word if you can think of an everyday English equivalent.

    line 47

“Common” is measured: kept by at least 6 in 10 of the 167 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md
<!-- forgeflow-capability-selection:start -->

Automatic capability selection

Resolve select-capabilities.js from the checkout scripts/forgeflow, a host-supplied plugin root, or the installed ForgeFlow runtime for this host. Run node <helper-dir>/select-capabilities.js --guide and follow the shared selection procedure with phase plan and the current objective, criteria and affected scope. Reuse the same result across alias handoffs and pass it through existing context construction; do not reset reassessment limits. Missing runtime support is an explicit limitation, not a reason to invent selection results. Preserve current workflow read-only and isolation boundaries. Planned capabilities are not executable and selection grants no new authority.

<!-- forgeflow-capability-selection:end -->

At workflow entry, run node <helper-dir>/open-session-dashboard.js --root <project-root> --workflow plan when available. Resolve <helper-dir> from the checkout's scripts/forgeflow first, then ${CODEX_HOME:-$HOME/.codex}/forgeflow/scripts/forgeflow. The helper starts or reuses agent-chat and reports known workflow phases on each entry; it uses CODEX_THREAD_ID, CLAUDE_SESSION_ID, or FORGEFLOW_SESSION_ID to open the local dashboard once per session. If the host supplies a session id separately, pass --session <host-session-id>; never invent a new id per invocation. Headless runs and FORGEFLOW_DASHBOARD_AUTO_OPEN=off skip the launch. A missing helper or unavailable browser must not block the workflow. Report actual phase transitions, significant progress, waiting, and the final result with node <runtime-root>/services/agent-chat/client.js activity <state> "<short label>" (<runtime-root> is the checkout or installed forgeflow directory). Use complete only when work and required checks have finished; report failed for failures, and never invent progress to keep Ember moving.

Use this skill when the user wants a concrete implementation plan before consultation or coding.

Resolve helpers before running them: set FORGEFLOW_HELPER_DIR to scripts/forgeflow when that directory exists, otherwise to ${CODEX_HOME:-$HOME/.codex}/forgeflow/scripts/forgeflow. If neither exists, report a missing Codex runtime installation.

Before other work, run:

"$FORGEFLOW_HELPER_DIR/ensure-forgeflow-state.sh"

Workflow:

  1. Build compact local memory context with scripts/forgeflow/build-memory-context.js when available, then load current discussion and research artifacts from .forgeflow/<project-name>/ when needed.
  2. Gather focused local context such as CONTEXT.md.
  3. Spawn product_lead_planner and coordinator_early in parallel.
  4. Synthesize the result into a unified implementation plan.
  5. Save it to .forgeflow/<project-name>/current-plan.md when appropriate.

Output should include:

  • phases and deliverables
  • in-scope / out-of-scope / deferred
  • dependencies and coordination risks
  • accessibility checklist
  • success criteria

Writing for CLI output

Apply George Orwell's six rules to progress updates, agent reports, and final summaries:

  1. Never use a metaphor, simile, or other figure of speech which you are used to seeing in print.
  2. Never use a long word where a short one will do.
  3. If it is possible to cut a word out, always cut it out.
  4. Never use the passive where you can use the active.
  5. Never use a foreign phrase, a scientific word, or a jargon word if you can think of an everyday English equivalent.
  6. Break any of these rules sooner than say anything outright barbarous.

Lead with the result or next action and its effect on the user's task. Match their technical background and requested detail. Explain an unfamiliar term when needed; retain precise terms for specialist reports. Use a calm, conversational voice and natural contractions. These rules take precedence over persona style and sample prose.

Use connected, short paragraphs with natural sentence variation. Use lists for steps or comparisons and headings when they help navigation. Cut repeated openings, stock transitions, rhetorical questions, forced praise, persona banter, and em dashes in prose. Warmth comes from noticing the user's actual concern and helping them act.

Progress updates should explain a finding, decision, blocker, or what the next check will resolve. Avoid narrating each tool call or repeating the plan. Ask only for information or authorization needed to proceed; explain why it matters. Final replies should stand alone: state what changed, why, what was checked, and any remaining action. Scale the detail to the task. Summarize routine checks; include tool names, versions, and internal counts only when they affect the reader's next decision. Keep validation gaps explicit.

Replace vague benefits with observable behavior. Use a brief example when it clarifies the change; label hypothetical examples. Never invent measurements, personal experiences, user reactions, test results, or approvals to make writing vivid. Keep uncertainty and failures explicit.

Preserve exact commands, code, paths, identifiers, error text, schema keys, verdict labels, and required evidence. Keep required report sections and machine-readable formats; apply style changes only to their prose. JSON-only outputs stay JSON-only. Before sending, check for awkward rhythm, repetition, unsupported claims, and whether the reader can tell what happens next. Clarity and faithful evidence are the goal; detector scores are not a quality gate.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.