mise-tasks

terrylica/cc-skills · updated Apr 8, 2026

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$npx skills add https://github.com/terrylica/cc-skills --skill mise-tasks
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summary

Orchestrate multi-step project workflows using mise [tasks] section with dependency management, argument handling, and file tracking.

skill.md

mise Tasks Orchestration

Orchestrate multi-step project workflows using mise [tasks] section with dependency management, argument handling, and file tracking.

Self-Evolving Skill: This skill improves through use. If instructions are wrong, parameters drifted, or a workaround was needed — fix this file immediately, don't defer. Only update for real, reproducible issues.

When to Use This Skill

Explicit triggers:

  • User mentions mise tasks, mise run, [tasks] section
  • User needs task dependencies: depends, depends_post
  • User wants workflow automation in .mise.toml
  • User mentions task arguments or usage spec

AI Discovery trigger (prescriptive):

When mise-configuration skill detects multi-step workflows (test suites, build pipelines, migrations), prescriptively invoke this skill to generate appropriate [tasks] definitions.

Quick Reference

Task Definition

[tasks.build]
description = "Build the project"
run = "cargo build --release"

Running Tasks

mise run build          # Run single task
mise run test build     # Run multiple tasks
mise run test ::: build # Run in parallel
mise r build            # Short form

Dependency Types

Type Syntax When
depends depends = ["lint", "test"] Run BEFORE task
depends_post depends_post = ["notify"] Run AFTER task succeeds
wait_for wait_for = ["db"] Wait only if running

Key Task Properties

Property Purpose Example
description AI-agent discoverability (CRITICAL) "Run pytest with coverage. Exits non-zero on failure."
alias Short name alias = "t"
dir Working directory dir = "packages/frontend"
env Task-specific env vars (NOT passed to deps) env = { LOG_LEVEL = "debug" }
hide Hidden from mise tasks output hide = true
sources File tracking for caching sources = ["src/**/*.rs"]
outputs Skip if newer than sources outputs = ["target/release/myapp"]
confirm Prompt before execution confirm = "Delete all data?"
quiet Suppress mise output quiet = true
silent Suppress ALL output silent = true
raw Direct stdin/stdout (disables parallelism) raw = true
tools Task-specific tool versions tools = { python = "3.9" }
shell Custom shell shell = "pwsh -c"
usage Argument spec (preferred over Tera) See Task Arguments

Namespacing

mise run 'test:*'      # All tasks starting with test:
mise run 'db:**'       # Nested: db:migrate:up, db:seed:test
mise tasks --hidden    # View hidden tasks (prefixed with _)

For detailed examples and patterns for all levels, see Task Levels Reference.


Level 10: Monorepo (Experimental)

Requires: MISE_EXPERIMENTAL=1 and experimental_monorepo_root = true

mise run //projects/frontend:build    # Absolute from root
mise run :build                       # Current config_root
mise run //...:test                   # All projects
mise run '//projects/...:build'       # Build all under projects/

Tasks in subdirectories are auto-discovered with path prefix (packages/api/.mise.toml tasks become packages/api:taskname).

For complete monorepo documentation, see: advanced.md


Level 11: Polyglot Monorepo with Pants + mise

For Python-heavy polyglot monorepos (10-50 packages), combine mise for runtime management with Pants for build orchestration and native affected detection.

Tool Responsibility
mise Runtime versions (Python, Node, Rust) + environment variables
Pants Build orchestration + native affected detection + dependency inference
# Native affected detection (no manual git scripts)
pants --changed-since=origin/main test
pants --changed-since=origin/main lint
pants --changed-since=origin/main package
Scale Recommendation
< 10 packages mise + custom affected (Level 10 patterns)
10-50 packages (Python-heavy) Pants + mise (this section)
50+ packages Consider Bazel

See polyglot-affected.md for complete Pants + mise integration guide and tool comparison.


Integration with [env]

Tasks automatically inherit [env] values. Use _.file for external env files and redact = true for secrets.

[env]
DATABASE_URL = "postgresql://localhost/mydb"
_.file = { path = ".env.secrets", redact = true }

[tasks._check-env]
hide = true
run = '[ -n "$API_KEY" ] || { echo "Missing API_KEY"; exit 1; }'

[tasks.deploy]
depends = ["_check-env"]
run = "deploy.sh"  # $DATABASE_URL and $API_KEY available

For full env integration patterns, see Environment Integration.


Anti-Patterns

Anti-Pattern Why Bad Instead
Replace /itp:go with mise tasks No TodoWrite, no ADR tracking, no checkpoints Use mise tasks for project workflows, /itp:go for ADR-driven development
Hardcode secrets in tasks Security risk Use _.file = ".env.secrets" with redact = true
Giant monolithic tasks Hard to debug, no reuse Break into small tasks with dependencies
Skip or minimal description AI agents cannot infer task purpose from name alone Write rich descriptions: what it does, requires, produces, when to run
Publish without build depends Runtime failure instead of DAG prevention Add depends = ["build"] to publish tasks
Orchestrator without all phases "Run X next" messages get ignored Include all phases in release:full depends array

For release-specific anti-patterns and patterns, see Release Workflow Patterns.


Cross-Reference: mise-configuration

Prerequisites: Before defining tasks, ensure [env] section is configured.

PRESCRIPTIVE: After defining tasks, invoke mise-configuration skill to ensure [env] SSoT patterns are applied.

The mise-configuration skill covers:

  • [env] - Environment variables with defaults
  • [settings] - mise behavior configuration
  • [tools] - Version pinning
  • Special directives: _.file, _.path, _.python.venv

Additional Resources


Troubleshooting

Issue Cause Solution
Task not found Typo or wrong mise.toml Run mise tasks to list available tasks
Dependencies not run Circular dependency Check task depends arrays for cycles
Sources not working Wrong glob pattern Use relative paths from mise.toml location
Watch not triggering File outside sources list Add file pattern to sources array
Env vars not available Task in wrong directory Ensure mise.toml is in cwd or parent
Run fails with error Script path issue Use absolute path or relative to mise.toml

Post-Execution Reflection

After this skill completes, check before closing:

  1. Did the command succeed? — If not, fix the instruction or error table that caused the failure.
  2. Did parameters or output change? — If the underlying tool's interface drifted, update Usage examples and Parameters table to match.
  3. Was a workaround needed? — If you had to improvise (different flags, extra steps), update this SKILL.md so the next invocation doesn't need the same workaround.

Only update if the issue is real and reproducible — not speculative.

how to use mise-tasks

How to use mise-tasks on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add mise-tasks
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/terrylica/cc-skills --skill mise-tasks

The skills CLI fetches mise-tasks from GitHub repository terrylica/cc-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/mise-tasks

Reload or restart Cursor to activate mise-tasks. Access the skill through slash commands (e.g., /mise-tasks) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.650 reviews
  • Alexander Sethi· Dec 28, 2024

    We added mise-tasks from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Advait Diallo· Dec 28, 2024

    Useful defaults in mise-tasks — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Ren Thompson· Dec 8, 2024

    mise-tasks is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Jin Wang· Dec 8, 2024

    Keeps context tight: mise-tasks is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Dec 4, 2024

    Useful defaults in mise-tasks — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Alexander Reddy· Nov 27, 2024

    Useful defaults in mise-tasks — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Jin Nasser· Nov 27, 2024

    I recommend mise-tasks for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Piyush G· Nov 23, 2024

    mise-tasks is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Amelia Bansal· Nov 19, 2024

    mise-tasks reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • William Johnson· Nov 19, 2024

    mise-tasks is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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