affaan-m/ECC

dynamic-workflow-mode

Design task-local harnesses, eval gates, and reusable skill extraction for Claude dynamic workflow mode and other adaptive agent harnesses.

81CollectingRuns scripts
See how to use itView GitHub source
npx skills add https://github.com/affaan-m/ECC --skill "skills/dynamic-workflow-mode"
Automated source guide

Source checked Jul 28, 2026·Refresh due Oct 26, 2026

Reorganized from the pinned upstream SKILL.md

Turn dynamic-workflow-mode's source instructions into a guide you can follow

According to the pinned SKILL.md from affaan-m/ECC: Use this skill when a coding agent can generate or adapt a task-local harness instead of only following a static command flow. The goal is to turn dynamic workflow mode into a disciplined system: temporary harnesses for one-off work, shared skill extraction for repeated work, an…

npx skills add https://github.com/affaan-m/ECC --skill "skills/dynamic-workflow-mode"
Check the pinned source

Best fit

  • Design task-local harnesses, eval gates, and reusable skill extraction for Claude dynamic workflow mode and other adaptive agent harnesses.

Bring this context

  • A concrete task that matches the documented purpose of dynamic-workflow-mode.
  • The files, examples, or context the task depends on.
  • Your constraints, target environment, and definition of done.

Expected outputs

  • The harness or skill path.
  • The eval commands and results.
  • The control pane or handoff artifact path.

Key source sections

Read dynamic-workflow-mode through these 5 source sections

Sections are extracted automatically from the pinned SKILL.md and link back to the source.

02

When To Activate

The user mentions dynamic workflows, custom harnesses, harness-per-task, adaptive workflows, or Claude Code dynamic workflow mode.

SKILL.md · When To Activate
The user mentions dynamic workflows, custom harnesses, harness-per-task, adaptive workflows, or Claude Code dynamic workflow mode.A task needs a custom loop, evaluator, crawler, fixture generator, watcher, or local dashboard.Multiple agents need the same repeatable process but the process is not yet captured as a shared skill.
03

Core Contract

Dynamic workflow mode should produce a task-local harness only when the harness is cheaper and safer than manually driving the same steps. The harness must have:

SKILL.md · Core Contract
Objective: the outcome it owns and the outcome it explicitly does not own.Inputs: files, URLs, prompts, data sources, credentials policy, and user-provided constraints.Outputs: commits, reports, screenshots, status files, or control pane snapshots.
04

Dynamic Harness Decision Tree

1. One-shot task: keep it inline. Do not invent a harness. 2. Repeated task with changing inputs: create a task-local harness and keep it under a temp or project-local working area. 3. Repeated task across teammates or repos: extract the pattern into a shared skill. 4. Task with…

SKILL.md · Dynamic Harness Decision Tree
One-shot task: keep it inline. Do not invent a harness.Repeated task with changing inputs: create a task-local harness and keep it under a temp or project-local working area.Repeated task across teammates or repos: extract the pattern into a shared skill.

SkillSignal prompt templates

Provide the task, context, and acceptance criteria

These prompts were written by SkillSignal from the source structure; they are not upstream text.

Task-start prompt

Confirm source fit, inputs, and outputs before acting.

Use dynamic-workflow-mode to help me with: [specific task]. Context: [files, data, or background]. Constraints: [environment, scope, and prohibited actions]. Before acting, check the pinned SKILL.md and explain which sections apply, what inputs are still missing, and what you will deliver.

Source-guided execution

Make the Agent explicitly follow the key extracted sections.

Apply the pinned dynamic-workflow-mode source to [task]. Pay particular attention to these source sections: “Dynamic Workflow Harness”, “When To Activate”, “Core Contract”, “Dynamic Harness Decision Tree”, “Task-Local Harness Template”. Preserve the important decision at each step. Mark facts not covered by the source as “needs confirmation” instead of inventing them. Then verify the result against my acceptance criteria: [criteria].

Result-review prompt

Check omissions, permissions, and source drift before delivery.

Review the current dynamic-workflow-mode result: (1) does it satisfy the original task; (2) were any applicable steps or limits in the pinned SKILL.md missed; (3) did it perform any unauthorized file, command, network, or data action; and (4) which conclusions remain unverified? List issues first, then fix only what the source or user authorization supports.

Output checklist

Verify each item before delivery

The task matches the purpose documented in the SKILL.md.

The source section “Dynamic Workflow Harness” has been checked.

The source section “When To Activate” has been checked.

The source section “Core Contract” has been checked.

The source section “Dynamic Harness Decision Tree” has been checked.

Inputs, constraints, and acceptance criteria are explicit.

Unverified facts, compatibility, and outcome claims are clearly marked.

Any file, command, network, or data action has been reviewed.

Choose a different workflow

When another Skill is the better fit

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Open source detail

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A separate implementation from MoizIbnYousaf/marketing-cli; compare its source, maintenance signals, and permission requirements.

Open source detail

arize-evaluator

Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.

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Open source detail

FAQ

What does dynamic-workflow-mode do?

Use this skill when a coding agent can generate or adapt a task-local harness instead of only following a static command flow. The goal is to turn dynamic workflow mode into a disciplined system: temporary harnesses for one-off work, shared skill extraction for repeated work, an…

How do I start using dynamic-workflow-mode?

The catalog detected this source-specific install command: npx skills add https://github.com/affaan-m/ECC --skill "skills/dynamic-workflow-mode". Inspect the command and pinned source before running it.

Which Agent platforms does it declare?

No dedicated Agent platform is declared in the pinned source record.

Repository stars
234,327
Repository forks
35,711
Quality
81/100
Source repository last pushed

Quality breakdown

Based on traceable docs and repository signals; stars are not treated as quality.

81/100
Documentation25/30
Specificity20/25
Maintenance20/20
Trust signals16/25

Compare before choosing

Related Agent Skills and source variants

These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.

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Use when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.

higgsfield-generate by MoizIbnYousaf

Use when the user wants to generate an image or video via Higgsfield AI. Covers 30+ models: Soul V2, Seedance 2.0, Kling 3.0, Veo 3.1, GPT Image 2, Nano Banana 2. Also covers Marketing Studio — branded ad video/image with avatars and products. Use whenever: "generate an image", "make a video", "animate this photo", "image-to-video", "img2vid", "edit this image with AI", "produce a clip", "create an ad", "make a UGC video", "marketing video", "brand video", "TV spot", "import product from URL", "

arize-evaluator by github

Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.

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Analyze Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.

scientific-brainstorming by k-dense-ai

Facilitates evidence-aware scientific ideation with independent generation, structured discussion, explicit assumptions, transparent evaluation, adversarial review, and decision logs. Use for early-stage research brainstorming or prioritizing candidate directions; hand off empirical validation, study design, ethics or regulatory review, and clinical questions to appropriate experts or skills.

View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 4 min

Dynamic Workflow Mode

Use this skill when a coding agent can generate or adapt a task-local harness instead of only following a static command flow. The goal is to turn dynamic workflow mode into a disciplined system: temporary harnesses for one-off work, shared skill extraction for repeated work, and observable control pane checkpoints for teams.

When To Activate

  • The user mentions dynamic workflows, custom harnesses, harness-per-task, adaptive workflows, or Claude Code dynamic workflow mode.
  • A task needs a custom loop, evaluator, crawler, fixture generator, watcher, or local dashboard.
  • Multiple agents need the same repeatable process but the process is not yet captured as a shared skill.
  • A workflow needs durable handoff artifacts, eval evidence, or operator approval before merge.

Core Contract

Dynamic workflow mode should produce a task-local harness only when the harness is cheaper and safer than manually driving the same steps. The harness must have:

  • Objective: the outcome it owns and the outcome it explicitly does not own.
  • Inputs: files, URLs, prompts, data sources, credentials policy, and user-provided constraints.
  • Outputs: commits, reports, screenshots, status files, or control pane snapshots.
  • Eval: at least one pass/fail check tied to the task, not only "it ran".
  • Handoff: a short artifact that tells the next operator what happened, what is blocked, and how to resume.

Dynamic Harness Decision Tree

  1. One-shot task: keep it inline. Do not invent a harness.
  2. Repeated task with changing inputs: create a task-local harness and keep it under a temp or project-local working area.
  3. Repeated task across teammates or repos: extract the pattern into a shared skill.
  4. Task with external state, queueing, or approvals: add control pane visibility before adding more automation.
  5. Task with safety risk: add an eval gate and a human merge gate before autonomous execution.

Task-Local Harness Template

Use this structure before writing code:

# Dynamic Workflow Harness

Objective:
- Ship:
- Do not ship:

Inputs:
- Repo or workspace:
- External systems:
- Credentials policy:

Loop:
1. Discover current state.
2. Generate or update the smallest useful artifact.
3. Run eval checks.
4. Record status and handoff.
5. Stop on failed gate, unclear ownership, or unsafe external action.

Eval:
- Command:
- Expected pass signal:
- Failure owner:

Handoff:
- Status:
- Evidence:
- Next action:

Shared Skill Extraction

Promote a task-local harness into a shared skill only when at least two of these are true:

  • The same workflow appears in multiple sessions, repos, teams, or launches.
  • The workflow needs specific language, tool, or safety sequencing.
  • Failures repeat because operators skip a gate or lose context.
  • The workflow has a stable input/output contract.
  • The workflow benefits from a control pane, status board, or team handoff.

When extracting, write the skill first in skills/<name>/SKILL.md. Add command shims only if a legacy slash-entry surface is still required.

Control Pane Checkpoints

Dynamic workflow mode becomes team-usable when it exposes state. Record these checkpoints whenever the task spans more than one session:

  • Plan: objective, owner, acceptance criteria, and risky external systems.
  • Queue: work items, assigned agent role, branch/worktree, and dependency edges.
  • Run: active harness, current loop step, recent eval result, and token/cost signal if available.
  • Gate: test results, browser screenshots, security review, and merge readiness.
  • Handoff: what is done, what failed, what needs a human decision.

If the repo has ECC2 state enabled, prefer adding or reading checkpoints through the ECC control pane or state-store-backed scripts instead of scattering untracked notes.

Eval Gates

Every dynamic harness needs a task-specific eval. Pick the cheapest reliable gate:

Work TypeEval Gate
Code featureFocused test, lint, coverage, and one integration path
UI/control paneBrowser smoke with screenshot and overflow/error checks
Agent workflowFixture transcript or seeded work item with expected routing
Research/contentSource-neutral brief, claim checklist, and publish-ready outline
IntegrationDry-run command, config validation, and no-secret scan

Do not claim a dynamic workflow is reusable until the eval can be rerun by another teammate.

Anti-Patterns

  • Generating scripts that hide the real decision logic from the operator.
  • Treating dynamic workflow mode as permission to skip tests.
  • Creating one-off docs when a shared skill or status artifact is the real product.
  • Running multiple agents without ownership, merge gate, or conflict policy.
  • Letting raw private research data leak into public docs.

Output Standard

Finish with:

  • The harness or skill path.
  • The eval commands and results.
  • The control pane or handoff artifact path.
  • The next reusable extraction candidate.
Source repo
affaan-m/ECC
Skill path
skills/dynamic-workflow-mode/SKILL.md
Commit SHA
4e973d3eaf92
Repository license
MIT
Data collected