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 skills/orin-dx/agent-plugins/plannpx skills add orin-dx/agent-plugins --skill plangit clone --depth 1 https://github.com/orin-dx/agent-pluginsWhat 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 | $0.00161 | $0.00921 |
| Opus 5 | $0.00081 | $0.00461 |
| Sonnet 5 | $0.00032 | $0.00184 |
| Haiku 4.5 | $0.00016 | $0.00092 |
Grade A, and why
plan 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 yesterday.
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.
What it actually says
Navigator Planning Skill
navigator is one skill, plan. Behavior adapts to what's asked, dispatching to whichever agent below fits the request — there is no separate navigator/estimate or navigator/challenge skill to invoke; estimating and challenging both happen inside this one skill.
-
Decompose a spec into a plan —
plannerreads a spec@1, produces an ordered sequence of implementation tasks (exact file paths, a failing test, minimal implementation, expected test output, a commit message, covers_criteria), and groups tasks into cohesive Subsystem Batches aligned with crate/package compilation boundaries as part of that decomposition — not a separate step. Reads the spec from disk at spec_file_path when set, and propagates spec_file_path, spec_hash, and linked_requirement into the plan@1 output. Also runs in amend mode: given an existing plan@1, a corrected spec@1, and the criterion_ids that changed, patches only the affected tasks instead of re-decomposing the whole plan. -
Estimate an existing plan —
estimatorassigns effort estimates (in minutes) to each task in a plan@1, identifies parallelizable tasks, and surfaces blocking dependencies. -
Challenge a draft plan —
challengeradversarially reviews a plan@1 for missing tasks, wrong ordering, under-specified steps, over-sized tasks, missing error handling, and acceptance criteria orphaned from every task's covers_criteria. An amended plan (from planner's amend mode) is not exempt from this review.
<subagent_dispatch_matrix>
| Agent | Role | Model / Effort | Delegate When |
|---|---|---|---|
| planner | Plan author | sonnet / medium | Decompose a spec into ordered, subsystem-batched implementation tasks. |
| estimator | Effort estimator | sonnet / medium | Assign time estimates, identify parallelizable tasks, and surface blocking dependencies. |
| challenger | Adversarial reviewer | sonnet / medium | Stress-test a draft plan@1 (max 2 review rounds) before any implementation begins. |
</subagent_dispatch_matrix>
<artifact_contracts>
Consumes: spec@1 (or its spec_file_path, read from disk when set)
Produces: plan@1 — carries spec_file_path, spec_hash, and linked_requirement propagated from the source spec
</artifact_contracts>
<tdd_requirement>
Every task in a plan@1 follows this exact sequence:
- Write the failing test
- Run the test — confirm it fails with the expected error
- Write the minimal implementation to make the test pass
- Run the test — confirm it passes
- Commit with the conventional commit message
A task that starts with implementation before a failing test violates this requirement.
</tdd_requirement>
<no_placeholders_rule>
Every step must show exact code. "Implement the feature", "add appropriate error handling", and "write tests as needed" are not steps — they are abdications. If the exact code is not known, it must be derived from the spec and documented as a concrete choice, not deferred as a TBD.
</no_placeholders_rule>
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.
- yesterday First seen · 72 lines · 161 tokens per session scan A 52a8b5437af0
plan is a skill published in the GitHub repository orin-dx/agent-plugins (1 stars, last pushed 5d ago), licensed MIT. It adds 161 tokens to every session and 921 once invoked, about $0.0008 per session on Opus 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 2026-08-31.
Other skills, from other repositories
campus-assignment-cleaner
Activates when a student or campus developer needs to make a working-but-messy codebase submission-ready before uploading it for grading. Trigger phrasings include "clean up my assignment before submitting", "remove debug prints and commented code", "tidy this up before I upload it to Moodle/Canvas/GitHub Classroom"…
peon-ping-log
Log exercise reps for the Peon Trainer. Use when user says they did pushups, squats, or wants to log reps. Examples - "/peon-ping-log 25 pushups", "/peon-ping-log 30 squats", "log 50 pushups".
agy-delegate
Delegate a coding task to the Google Antigravity CLI (agy) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Antigravity or agy - phrasings like "have Antigravity do X", "delegate this to agy", "run it through agy", or "use…
conductor-implement
Executes the tasks defined in the specified track's plan. Use this to start or continue working on a feature, bug fix, or chore.
hyperpod-version-checker
Check and compare software component versions on SageMaker HyperPod cluster nodes - NVIDIA drivers, CUDA toolkit, cuDNN, NCCL, EFA, AWS OFI NCCL, GDRCopy, MPI, Neuron SDK (Trainium/Inferentia), Python, and PyTorch. Use when checking component versions, verifying CUDA/driver compatibility, detecting version mismatches…
dsql
Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, diagnose cluster performance, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, FK…