Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/kubiyabot/skill/project-statusgit clone --depth 1 https://github.com/kubiyabot/skillWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00426 |
| Opus 5 | $0.00000 | $0.00213 |
| Sonnet 5 | $0.00000 | $0.00085 |
| Haiku 4.5 | $0.00000 | $0.00043 |
Grade A, and why
project-status scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to project-status — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Enhanced status command with comprehensive project insights.
Arguments: $ARGUMENTS
Intelligent Status Overview
1. Executive Summary
Quick dashboard view:
- 🏃 Active work (in-progress tasks)
- 📊 Progress metrics (% complete, velocity)
- 🚧 Blockers and risks
- ⏱️ Time analysis (estimated vs actual)
- 🎯 Sprint/milestone progress
2. Contextual Analysis
Based on $ARGUMENTS, focus on:
- "sprint" → Current sprint progress and burndown
- "blocked" → Dependency chains and resolution paths
- "team" → Task distribution and workload
- "timeline" → Schedule adherence and projections
- "risk" → High complexity or overdue items
3. Smart Insights
Workflow Health:
- Idle tasks (in-progress > 24h without updates)
- Bottlenecks (multiple tasks waiting on same dependency)
- Quick wins (low complexity, high impact)
Predictive Analytics:
- Completion projections based on velocity
- Risk of missing deadlines
- Recommended task order for optimal flow
4. Visual Intelligence
Dynamic visualization based on data:
Sprint Progress: ████████░░ 80% (16/20 tasks)
Velocity Trend: ↗️ +15% this week
Blocked Tasks: 🔴 3 critical path items
Priority Distribution:
High: ████████ 8 tasks (2 blocked)
Medium: ████░░░░ 4 tasks
Low: ██░░░░░░ 2 tasks
5. Actionable Recommendations
Based on analysis:
- Immediate actions (unblock critical path)
- Today's focus (optimal task sequence)
- Process improvements (recurring patterns)
- Resource needs (skills, time, dependencies)
6. Historical Context
Compare to previous periods:
- Velocity changes
- Pattern recognition
- Improvement areas
- Success patterns to repeat
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 64 lines · 0 tokens per session scan A c7da48edf158
project-status is a command published in the GitHub repository kubiyabot/skill (16 stars, last pushed 7mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 426 tokens. A static security scan graded it A with 0 findings. It is 100% identical to project-status, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.