Agent skill

Kanban Run

by cyanluna-git in cyanluna-git/cyanluna.skills

Run the AI team pipeline for kanban tasks — orchestration loop with 6 agents (Planner, Critic, Builder, Shield, Inspector, Ranger), single-step execution, and code review.

MITAuto-check passedProductivity & Automation

Install Kanban Run

skills CLI
$ npx skills add cyanluna-git/cyanluna.skills --skill kanban-run -a claude-code

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

GitHub CLI
$ gh skill install cyanluna-git/cyanluna.skills kanban-run --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/cyanluna-git/cyanluna.skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/kanban-run .claude/skills/kanban-run && 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
kanban-run
GitHub stars
183
Token cost
~4.3k tokens
SKILL.md length
952 words
Files
1
Skills in repo
16
Repo updated
First seen
Licence
MIT

At a glance

Run the AI team pipeline for kanban tasks — orchestration loop with 6 agents (Planner, Critic, Builder, Shield, Inspector, Ranger), single-step execution, and code review.

  • Works in 3 steps: User mentions a kanban task ID and… → Claude has proposed implementing a… → User says "next task" / "continue" / "다음…
  • : user says implement task NNN
  • SKILL.md covers Auto-Trigger Rules and Commands
  • Calls curl, jq and python3

What it does

Kanban Run is an agent skill from cyanluna-git/cyanluna.skills. Run the AI team pipeline for kanban tasks — orchestration loop with 6 agents (Planner, Critic, Builder, Shield, Inspector, Ranger), single-step execution, and code review. Use /kanban-run to execute tasks through the 7-column pipeline. AUTO-TRIGGER when: user says "implement task NNN" or any task ID + implement/build/do combination; or user confirms with "yes/ok/go/do it" after Claude proposes implementing a specific kanban task.

Its SKILL.md is about 4.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Productivity & Automation, covering Task management. The licence is MIT.

When your agent uses it

  • : user says implement task NNN
  • Any task ID + implement/build/do combination
  • User confirms with yes/ok/go/do it after Claude proposes implementing a specific kanban task

Example prompts

  • “implement task NNN”
  • “yes/ok/go/do it”
  • “/kanban-run”

Requirements

  • Python 3

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. User mentions a kanban task ID and requests implementation
  2. Claude has proposed implementing a specific kanban task and the user confirms
  3. User says "next task" / "continue" / "다음 태스크 해줘" when a task is in progress

What it can do on your machine

Read from SKILL.md and the folder at commit df5be37. 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

    Shell commands in SKILL.md call:

    • curl
    • jq
    • python3
    • git

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

  • Network

    No URLs in SKILL.md. Its commands use curl and git, which can reach the network depending on how they are called.

    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

Kanban Run loads about 4.3k tokens when it runs. Until then it costs about 111 tokens; SKILL.md has 952 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~111
When it runs · the whole SKILL.md, loaded when a task matches
~4.3k

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 cyanluna-git/cyanluna.skills at commit df5be37, republished under its MIT licence (© cyanluna-git). 952 words, ~4,255 tokens.

Download SKILL.mdSave it as .claude/skills/kanban-run/SKILL.md (or your agent's skills folder).
name
kanban-run
description
Run the AI team pipeline for kanban tasks — orchestration loop with 6 agents (Planner, Critic, Builder, Shield, Inspector, Ranger), single-step execution, and code review. Use /kanban-run to execute tasks through the 7-column pipeline. AUTO-TRIGGER when: user says "implement task NNN" or any task ID + implement/build/do combination; or user confirms with "yes/ok/go/do it" after Claude proposes implementing a specific kanban task.
license
MIT

Auto-Trigger Rules

ALWAYS invoke this skill (without waiting for /kanban-run) when:

  1. User mentions a kanban task ID and requests implementation:

    • "implement task #NNN" / "build task NNN" / "do NNN" / "run NNN"
    • Korean equivalents: "태스크 NNN 구현해줘" / "NNN 해줘" / "NNN 번 작업해줘"
    • Any message pairing a task number with implement / build / work on / do
  2. Claude has proposed implementing a specific kanban task and the user confirms:

    • Pattern: Claude says "Shall I implement task #NNN [title]?" → User replies "yes", "ok", "go", "do it", "응", "해줘", "그래", "ㅇㅇ"
    • This confirmation must trigger /kanban-run <ID> automatically — do not implement manually
  3. User says "next task" / "continue" / "다음 태스크 해줘" when a task is in progress:

    • Fetch board context first, identify next todo task, then run it

When auto-triggered: extract task ID and call /kanban-run <ID> — never implement code manually and patch kanban state afterward.

Shared context: read ../kanban/shared.md for DB path, pipeline levels, status transitions, DB operations, error handling, and agent context flow. Safety principles: read ../kanban/principles.md — mandatory, not optional. Schema: read ../kanban/schema.md for full DB schema, column descriptions, and JSON field formats.

Commands

In Codex environments, this skill may be invoked directly as a slash command text such as $kanban-run <ID> or $kanban-run <ID> --auto.

/kanban-run step <ID> — Single Step

Execute only the next pipeline step then exit. Same logic as /kanban-run but no loop.

/kanban-run <ID> [--auto] — Run Full Pipeline

Default: pause for user confirmation at Plan Review and Impl Review approvals. --auto: fully automatic (circuit breaker still fires).

Orchestration Loop (Level-Aware)
L1 Quick:
  todo → Worker(builder) implements → commit → done

L2 Standard:
  todo → Plan Agent(planner) → impl (skip plan_review)
  impl → Worker(builder) + TDD Tester(shield) → impl_review
  impl_review → Code Review → [user confirm] → commit → done / reject → impl

L3 Full:
  todo → Plan Agent(planner) → plan_review
  plan_review → Review Agent(critic) → [user confirm: y/c/n] → impl / ceo-review / reject→plan
    └─ [c] CEO Review: product angle check → update plan → back to plan_review
  impl → Worker(builder) + TDD Tester(shield) → impl_review
  impl_review → Code Review(inspector) → [user confirm] → test / reject → impl
  test → Test Runner(ranger) → pass → commit → done / fail → impl

Circuit breaker: plan_review_count > 3 OR impl_review_count > 3 → stop, ask user

CEO Review (L3 plan_review only)

When the user selects [c] at the plan_review confirmation prompt, run a CEO-perspective analysis inline before proceeding to impl. Not a separate agent — run as a structured prompt to the current model:

Adopt the perspective of a skeptical product founder reviewing this plan.
Ask:
  (1) Is this feature actually necessary, or can the need be met more simply?
  (2) Does this align with the project's stated purpose? [load from project brief]
  (3) Is there a 10x simpler implementation that solves 80% of the problem?
  (4) What might we regret about this decision in 6 months?
Output: bullet list of concerns, or "No concerns — looks right-sized."

After CEO review output, present: [y] proceed to impl / [r] revise plan / [n] reject

Read the task's level field first to determine which steps to execute.

Model Routing (Provider-Aware)

Resolve real model names from ../kanban/models.json using provider:

  • KANBAN_MODEL_PROVIDER env var if set (claude or codex)
  • else codex when CODEX_* env is present
  • else claude when CLAUDE_* env is present
  • else claude when .claude/ exists
  • else codex when .codex/ exists
  • else default_provider from models.json

For Codex, the router should prefer the higher-capability entries in models.json for the full kanban-run pipeline.

bash
MODEL_PROVIDER=${KANBAN_MODEL_PROVIDER:-}
if [ -z "$MODEL_PROVIDER" ] && [ -n "${CODEX_THREAD_ID:-}${CODEX_CI:-}" ]; then MODEL_PROVIDER=codex; fi
if [ -z "$MODEL_PROVIDER" ] && [ -n "${CLAUDE_PROJECT_DIR:-}${CLAUDECODE:-}" ]; then MODEL_PROVIDER=claude; fi
if [ -z "$MODEL_PROVIDER" ] && [ -d .claude ]; then MODEL_PROVIDER=claude; fi
if [ -z "$MODEL_PROVIDER" ] && [ -d .codex ]; then MODEL_PROVIDER=codex; fi

read_model() {
  local key="$1"
  python3 - "$MODEL_PROVIDER" "$key" <<'PY'
import json, pathlib, sys
p = pathlib.Path("../kanban/models.json")
d = json.loads(p.read_text())
provider = sys.argv[1] or d["default_provider"]
key = sys.argv[2]
print(d["providers"][provider][key])
PY
}

read_effort() {
  local key="$1"
  python3 - "$MODEL_PROVIDER" "$key" <<'PY'
import json, pathlib, sys
p = pathlib.Path("../kanban/models.json")
d = json.loads(p.read_text())
provider = sys.argv[1] or d["default_provider"]
key = sys.argv[2]
print(d.get("reasoning_effort", {}).get(provider, {}).get(key, ""))
PY
}

MODEL_PLANNER=$(read_model planner)
MODEL_CRITIC=$(read_model critic)
MODEL_BUILDER=$(read_model builder)
MODEL_SHIELD=$(read_model shield)
MODEL_INSPECTOR=$(read_model inspector)
MODEL_RANGER=$(read_model ranger)
EFFORT_PLANNER=$(read_effort planner)
EFFORT_CRITIC=$(read_effort critic)
EFFORT_BUILDER=$(read_effort builder)
EFFORT_SHIELD=$(read_effort shield)
EFFORT_INSPECTOR=$(read_effort inspector)
EFFORT_RANGER=$(read_effort ranger)
Implementation
bash
# 1. Read current task state (status + level only)
TASK=$(curl -s "${AUTH_HEADER[@]}" "$BASE_URL/api/task/$ID?project=$PROJECT&fields=status,level")
STATUS=$(echo "$TASK" | jq -r '.status')

# 2. Dispatch agent (see Agent Dispatch below)
# 3. After agent: append to agent_log (see schema.md for format)
# 4. Re-read state, loop until done or circuit breaker
Agent Nicknames & Identity

Each agent has a fixed nickname used consistently across all records. The task card becomes a work log — every field and every log entry is signed.

NicknameRoleModel KeyReasoning Effort (codex)Status trigger
PlannerPlan Agentplannerhightodo
CriticPlan Review Agentcriticmediumplan_review
BuilderWorker Agentbuilderhighimpl (step 1)
ShieldTDD Testershieldmediumimpl (step 2)
InspectorCode Review Agentinspectormediumimpl_review
RangerTest Runnerrangermediumtest

See ../kanban/schema.md for JSON formats and the Signature Header Rule.

Agent Dispatch

Template files are at ../kanban/templates/.

StatusTemplateNicknameModel Key
todotemplates/plan-agent.mdPlannerplanner
plan_reviewtemplates/review-agent.mdCriticcritic
impl step 1templates/worker-agent.mdBuilderbuilder
impl step 2templates/tdd-tester.mdShieldshield
impl_reviewtemplates/code-review-agent.mdInspectorinspector
testtemplates/test-runner.mdRangerranger

Agent minimum fields (fetch only what each agent needs):

NicknameRequired Fields
Plannertitle,description,plan_review_comments
Critictitle,description,plan,decision_log,done_when
Buildertitle,description,plan,done_when,plan_review_comments,review_comments
Shieldtitle,description,implementation_notes
Inspectortitle,description,plan,done_when,implementation_notes
Rangertitle,implementation_notes

Dispatch procedure — execute in this order for every agent:

⓪ Fetch project brief (once per pipeline run, cache for all agents)
   PROJECT_DATA = curl GET /api/projects/$PROJECT
   PROJECT_BRIEF = extract .brief field (empty string if null or project not found)
   This is injected into every agent template via <project_brief> placeholder.

⓪ʙ Resolve dependencies & review feedback (once per pipeline run, cache for all agents)

   **Parse dependencies from description:**
   ```bash
   # Extract dependency IDs from description (case-insensitive)
   DESCRIPTION=$(curl -s "${AUTH_HEADER[@]}" "$BASE_URL/api/task/$ID?project=$PROJECT&fields=description" | jq -r '.description // ""')
   DEP_IDS=$(echo "$DESCRIPTION" | grep -ioP 'Depends on:\s*\K#\d+(?:,\s*#\d+)*' | grep -oP '\d+' || true)

Circular dependency check: If $ID (current task) appears in any dependency's own Depends on: line, emit error and abort:

bash
for DEP_ID in $DEP_IDS; do
  DEP_TASK=$(curl -s "${AUTH_HEADER[@]}" "$BASE_URL/api/task/$DEP_ID?project=$PROJECT&fields=title,status,description,decision_log,implementation_notes")
  HTTP_CODE=$(echo "$DEP_TASK" | jq -r '.id // empty')
  if [ -z "$HTTP_CODE" ]; then
    echo "WARNING: dependency #$DEP_ID not found (404), skipping"
    continue
  fi
  DEP_DESC=$(echo "$DEP_TASK" | jq -r '.description // ""')
  if echo "$DEP_DESC" | grep -iqP "Depends on:.*#$ID\\b"; then
    echo "ERROR: circular dependency detected — #$ID ↔ #$DEP_ID. Aborting."
    exit 1
  fi
  # Cache: DEPS[$DEP_ID] = { title, status, decision_log, implementation_notes }
done

Build per-agent dependency context string: For each cached dependency, assemble context based on the current agent:

  • Planner: decision_log (500 chars) + implementation_notes (500 chars)
  • Builder: implementation_notes (500 chars)
  • Inspector: decision_log (300 chars)

Truncation: if field length > limit, take first N chars + ...[truncated]. If dep status != done: prepend [IN PROGRESS] warning to that dep's block. If no dependencies: DEPS_CONTEXT="" (empty string — placeholder removed cleanly).

Format per dependency:

### #<DEP_ID>: <title> [<status>]
[IN PROGRESS]

**Decision Log:**
<truncated decision_log>

**Implementation Notes:**
<truncated implementation_notes>

Extract review feedback for re-runs:

bash
# Critic feedback (for Planner re-run)
CRITIC_FEEDBACK=""
PLAN_REVIEW_COMMENTS=$(echo "$TASK" | jq -r '.plan_review_comments // ""')
if [ -n "$PLAN_REVIEW_COMMENTS" ] && [ "$PLAN_REVIEW_COMMENTS" != "null" ]; then
  CRITIC_FEEDBACK=$(echo "$PLAN_REVIEW_COMMENTS" | python3 -c "
import sys, json
data = json.load(sys.stdin)
if isinstance(data, list) and len(data) > 0:
  print(data[-1].get('comment', ''))
")
fi

# Inspector feedback (for Builder re-run)
INSPECTOR_FEEDBACK=""
REVIEW_COMMENTS=$(echo "$TASK" | jq -r '.review_comments // ""')
if [ -n "$REVIEW_COMMENTS" ] && [ "$REVIEW_COMMENTS" != "null" ]; then
  INSPECTOR_FEEDBACK=$(echo "$REVIEW_COMMENTS" | python3 -c "
import sys, json
data = json.load(sys.stdin)
if isinstance(data, list) and len(data) > 0:
  print(data[-1].get('comment', ''))
")
fi

① Read task fields (use per-agent fields to minimize token usage)

Show full SKILL.md (311 more words)Show less

Planner

TASK = curl GET /api/task/$ID?project=$PROJECT&fields=title,description,plan_review_comments

Critic

TASK = curl GET /api/task/$ID?project=$PROJECT&fields=title,description,plan,decision_log,done_when

Builder

TASK = curl GET /api/task/$ID?project=$PROJECT&fields=title,description,plan,done_when,plan_review_comments,review_comments

Shield

TASK = curl GET /api/task/$ID?project=$PROJECT&fields=title,description,implementation_notes

Inspector

TASK = curl GET /api/task/$ID?project=$PROJECT&fields=title,description,plan,done_when,implementation_notes

Ranger

TASK = curl GET /api/task/$ID?project=$PROJECT&fields=title,implementation_notes Extract only the fields listed above for each agent

② Mark agent as active curl PATCH /api/task/$ID → { "current_agent": "<Nickname>" }

③ Read template file Read tool: ../kanban/templates/<agent>.md

④ Fill placeholders in template Replace every occurrence of: <ID> → actual task ID <PROJECT> → actual project name <project_brief> → project brief from step ⓪ (empty string if not set) <title> → task title <description> → task description (requirements) <plan> → plan field value <decision_log> → decision_log field value <done_when> → done_when field value <implementation_notes> → implementation_notes field value <plan_review_comments> → plan_review_comments field value <dependencies_context> → per-agent dep context from step ⓪ʙ (empty string if none) <critic_feedback> → latest plan_review_comments comment (empty if first run) <inspector_feedback> → latest review_comments comment (empty if first run) <TIMESTAMP> → current UTC time (ISO 8601) <MODEL_PLANNER> → $MODEL_PLANNER <MODEL_CRITIC> → $MODEL_CRITIC <MODEL_BUILDER> → $MODEL_BUILDER <MODEL_SHIELD> → $MODEL_SHIELD <MODEL_INSPECTOR> → $MODEL_INSPECTOR <MODEL_RANGER> → $MODEL_RANGER <EFFORT_PLANNER> → $EFFORT_PLANNER <EFFORT_CRITIC> → $EFFORT_CRITIC <EFFORT_BUILDER> → $EFFORT_BUILDER <EFFORT_SHIELD> → $EFFORT_SHIELD <EFFORT_INSPECTOR> → $EFFORT_INSPECTOR <EFFORT_RANGER> → $EFFORT_RANGER

Recommended helper script:

bash
PROMPT=$(python3 ../kanban/scripts/render_agent_prompt.py \
  --template ../kanban/templates/<agent>.md \
  --models ../kanban/models.json \
  --provider "$MODEL_PROVIDER" \
  --set ID="$ID" \
  --set PROJECT="$PROJECT" \
  --set project_brief="$PROJECT_BRIEF" \
  --set title="$TITLE" \
  --set description="$DESCRIPTION" \
  --set plan="$PLAN" \
  --set decision_log="$DECISION_LOG" \
  --set done_when="$DONE_WHEN" \
  --set implementation_notes="$IMPLEMENTATION_NOTES" \
  --set plan_review_comments="$PLAN_REVIEW_COMMENTS" \
  --set dependencies_context="$DEPS_CONTEXT" \
  --set critic_feedback="$CRITIC_FEEDBACK" \
  --set inspector_feedback="$INSPECTOR_FEEDBACK" \
  --set TIMESTAMP="$TIMESTAMP")

If a field is missing, pass empty string (--set key=""). Use --strict only when every unresolved <...> token should be treated as an error.

⑤ Launch Task tool with filled prompt If MODEL_PROVIDER is codex: Task( subagent_type = "general-purpose", model = "<resolved model from models.json>", model_reasoning_effort= "<resolved effort from models.json>", prompt = <filled template content> )

Otherwise (claude): Task( subagent_type = "general-purpose", model = "<resolved model from models.json>", prompt = <filled template content> )

⑥ After Task completes — append signed entry to agent_log (use schema.md › "Appending to agent_log" snippet, set agent=<Nickname>, model=<model>, message=<summary>)


After Builder + Shield both complete, move to `impl_review`:
```bash
curl -s "${AUTH_HEADER[@]}" -X PATCH "$BASE_URL/api/task/$ID?project=$PROJECT" \
  -H 'Content-Type: application/json' \
  -d '{"status": "impl_review", "current_agent": null}'

Default mode: after plan_review and impl_review agents complete, ask user with AskUserQuestion to accept/reject before advancing. Auto mode (--auto): auto-accept the agent's decision.

→ Done Transition (all levels)
bash
# 1. Commit pending changes
if [ -n "$(git status --porcelain 2>/dev/null)" ]; then
  git add -A
  git commit -m "feat: <TITLE> [kanban #<ID>]"
fi
COMMIT_HASH=$(git rev-parse --short HEAD 2>/dev/null || echo "no-git")

# 2. Move to done
curl -s "${AUTH_HEADER[@]}" -X PATCH "$BASE_URL/api/task/$ID?project=$PROJECT" \
  -H 'Content-Type: application/json' \
  -d '{"status": "done"}'

# 3. Record commit hash in notes
curl -s "${AUTH_HEADER[@]}" -X POST "$BASE_URL/api/task/$ID/note?project=$PROJECT" \
  -H 'Content-Type: application/json' \
  -d "{\"content\": \"Commit: $COMMIT_HASH\"}"

If no commits yet, skip note or record "Commit: (none)".

/kanban-run review <ID> — Code Review

Trigger Code Review agent for a task in impl_review status (same as impl_review step).

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

Files

Just SKILL.md in kanban-run of cyanluna-git/cyanluna.skills.

Open the folder on GitHubat commit df5be37

Compare with similar skills

Kanban Run 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.

Kanban Run compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Kanban Run this skillcyanluna-git/cyanluna.skills183—~4.3kAutomated safety check: PassMIT
Superset Agent Standupsuperset-sh/superset15k—~712Automated safety check: PassCustom licence
AgentRQ Workspace Agentagentrq/agentrq1.1k—~1.9kAutomated safety check: PassAGPL-3.0
Markdown Task Managerioniks/MarkdownTaskManager535—~2.2kAutomated safety check: PassMPL-2.0
Pi Messenger Crewnicobailon/pi-messenger719—~3.7kAutomated safety check: PassNone
Codekanban CLIfy0/CodeKanban226—~2.7kAutomated safety check: PassApache-2.0

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Questions about Kanban Run

What does Kanban Run do?

Run the AI team pipeline for kanban tasks — orchestration loop with 6 agents (Planner, Critic, Builder, Shield, Inspector, Ranger), single-step execution, and code review. skills. Run the AI team pipeline for kanban tasks — orchestration loop with 6 agents (Planner, Critic, Builder, Shield, Inspector, Ranger), single-step execution, and code review.

When should I use Kanban Run?

Kanban Run fits situations like: : user says implement task NNN; any task ID + implement/build/do combination; user confirms with yes/ok/go/do it after Claude proposes implementing a specific kanban task.

How do I install Kanban Run in Claude Code?

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

How do I install Kanban Run in Codex?

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

Can I use Kanban Run 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 cyanluna-git/cyanluna.skills --skill kanban-run -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/kanban-run, .gemini/skills/kanban-run, .github/skills/kanban-run and .opencode/skills/kanban-run in your project.

What does Kanban Run need to run?

Going by SKILL.md and its folder, Kanban Run needs the command-line tools its instructions call (curl, jq, python3 and git). Our summary lists: Python 3.

Does Kanban Run access the network?

SKILL.md contains no URLs. Its commands use curl and git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Kanban Run 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 Kanban Run use?

Kanban Run is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Kanban Run use?

About 4.3k tokens (SKILL.md is roughly 17k 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 Kanban Run?

Skills that share tags, products or a category with Kanban Run: Superset Agent Standup (superset-sh/superset, 15k stars), AgentRQ Workspace Agent (agentrq/agentrq, 1.1k stars), Markdown Task Manager (ioniks/MarkdownTaskManager, 535 stars) and Pi Messenger Crew (nicobailon/pi-messenger, 719 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Kanban Run?

cyanluna-git (a GitHub user) maintains it in cyanluna-git/cyanluna.skills, which has 183 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on June 22, 2026.

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