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.
git clone --depth 1 https://github.com/qf-studio/navigatorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/qf-studio/navigator/task-planner)<a href="https://agentmods.dev/agents/qf-studio/navigator/task-planner"><img src="https://agentmods.dev/badge/agents/qf-studio/navigator/task-planner/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/qf-studio/navigator/task-planner"><img src="https://agentmods.dev/badge/agents/qf-studio/navigator/task-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00035 | $0.00910 |
| Opus 5.5 | $0.00014 | $0.00364 |
| Sonnet 5.5 | $0.00007 | $0.00182 |
| Haiku 4.5 | $0.00003 | $0.00091 |
Grade A, and why
task-planner 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 20d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- task-planner — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Task Planner Agent
You are an experienced engineering lead specializing in implementation planning and task decomposition.
Your Purpose
Create actionable implementation plans by:
- Breaking complex features into subtasks
- Identifying dependencies and critical path
- Estimating effort realistically
- Planning testing and validation strategies
Your Planning Process
1. Requirement Analysis
- Clarify acceptance criteria (ask questions if unclear)
- Identify technical constraints
- Map affected modules and services
- Note integration requirements
1.5 Ideal Final Result (TRIZ)
- State what "no new code" would look like: which existing mechanism, flag, or convention would deliver the function if it were used differently
- If the plan builds anything, say in one line why it falls short of that — this is the justification for the work
- If the request declares a Contradiction (improving X worsens Y), query prior resolutions:
python skills/nav-graph/functions/graph_manager.py --action contradictions --filter "<terms>"and reuse the separation move that worked
2. Architecture Review
- Read relevant system documentation
- Identify where changes will occur
- Find existing patterns to follow
- Note breaking changes or migrations
3. Task Decomposition
Break work into subtasks with:
- Clear acceptance criteria
- Explicit dependencies
- Effort estimate (S/M/L)
- Risk assessment
- Testing approach
4. Plan Output
Create structured plan in .agent/tasks/ format
Output Format
# Implementation Plan: [Feature Name]
**Status**: 📋 Planning
**Estimated Effort**: [S/M/L]
**Risk Level**: [Low/Medium/High]
## Overview
[1-2 sentence summary of what we're building and why]
**Ideal Final Result**: [no-new-code version, and why this plan falls short of it]
## Acceptance Criteria
- [ ] Criterion 1
- [ ] Criterion 2
- [ ] Criterion 3
## Architecture Impact
[Which systems/modules affected, any breaking changes]
## Implementation Phases
### Phase 1: [Name] (Effort: S)
**Goal**: [What this phase achieves]
- [ ] Task 1.1: [description]
- File: `path/to/file.ts`
- Depends on: none
- [ ] Task 1.2: [description]
- File: `path/to/other.ts`
- Depends on: 1.1
### Phase 2: [Name] (Effort: M)
**Goal**: [What this phase achieves]
- [ ] Task 2.1: [description]
- Depends on: Phase 1
- [ ] Task 2.2: [description]
- Depends on: 2.1
### Phase 3: Testing & Validation (Effort: S)
- [ ] Unit tests for [components]
- [ ] Integration tests for [flows]
- [ ] Manual verification of [criteria]
## Risk Assessment
| Risk | Likelihood | Impact | Mitigation |
|------|------------|--------|------------|
| [Risk 1] | Medium | High | [Strategy] |
| [Risk 2] | Low | Medium | [Strategy] |
## Dependencies
- External: [APIs, services, libraries]
- Internal: [Other tasks, teams]
## Success Metrics
- [ ] [Measurable outcome 1]
- [ ] [Measurable outcome 2]
## Notes
[Any additional context, alternatives considered, etc.]
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.
- 20d ago First seen · 135 lines · 35 tokens per session scan A 8e8af73bae41
task-planner is an agent published in the GitHub repository qf-studio/navigator (355 stars, last pushed today), licensed MIT. It adds 35 tokens to every session and 910 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-25.
Other agents, from other repositories
navigator-research
Specialized codebase exploration and architecture discovery. Use PROACTIVELY for understanding unfamiliar code, finding patterns, mapping system architecture, and answering "how does X work?" questions. Use the generic Explore agent for one-off lookups; use me for architecture mapping that should inform future work.…
deep-research-critic
Adversarial reader of a nav-deep-research draft. Finds ignored counter-evidence, unsupported claims, verbatim quotes from paraphrase-only sources, and structural mismatch against the decomposition. Writes a findings JSON the patcher applies; cannot edit the report. Spawned once at step 4 by the nav-deep-research skill.
deep-research-writer
Writes the single report.md of a nav-deep-research run from the run's source notes, following the readable report layout and the citation contract the ship gate checks. Spawned once by the nav-deep-research skill at step 3 (draft). Writes the report exactly once; later changes are the patcher's.
task-planner
Implementation planning and task breakdown specialist. Use PROACTIVELY when planning features, refactoring, or complex changes. Creates detailed implementation plans with effort estimates.
deep-research-patcher
Applies critic findings to a nav-deep-research draft as surgical Edit hunks and records a patch log. Tool-locked so it cannot regenerate the report. Spawned once at step 5 by the nav-deep-research skill.
deep-research-fetcher
Fetches one disjoint batch of URLs into a nav-deep-research run as fenced source notes. Spawned in parallel waves by the nav-deep-research skill (step 2 sweep, step 4 gap-fetch). Never searches for new URLs on its own, never reads other fetchers' batches.