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 skills add joshuadavidthomas/agent-skills --skill feature-planning-artifactsgit clone --depth 1 https://github.com/joshuadavidthomas/agent-skillsWrote 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/skills/joshuadavidthomas/agent-skills/feature-planning-artifacts)<a href="https://agentmods.dev/skills/joshuadavidthomas/agent-skills/feature-planning-artifacts"><img src="https://agentmods.dev/badge/skills/joshuadavidthomas/agent-skills/feature-planning-artifacts/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/skills/joshuadavidthomas/agent-skills/feature-planning-artifacts"><img src="https://agentmods.dev/badge/skills/joshuadavidthomas/agent-skills/feature-planning-artifacts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00073 | $0.02550 |
| Opus 5 | $0.00036 | $0.01275 |
| Sonnet 5 | $0.00015 | $0.00510 |
| Haiku 4.5 | $0.00007 | $0.00255 |
Grade A, and why
feature-planning-artifacts 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Planning Artifacts
Create or update staged HumanLayer-style planning artifacts for work that needs research, design judgment, vertical slicing, or an executor-safe plan before implementation.
This skill is not a one-shot plan generator. It should normally take an input, delegate or perform reconnaissance, write or revise the current-stage artifact, then stop at the review gate. Do not continue to the next artifact until the current one is accepted or the user explicitly asks to proceed.
Treat detailed planning as meta-work: each artifact should make future implementation safer by defining success, surfacing decisions, turning recurring choices into policy when appropriate, and specifying evals/regression checks.
Open and resolved questions live in the design discussion. Plan iteration updates the plan itself.
Source Frame
Before writing or updating planning artifacts, load what applies:
- The selected strategic-roadmap item, opportunity card, architecture candidate, or
NNN-*.mdplan. - Existing artifacts for this effort, especially the latest design discussion, outline, or plan.
- The
coding-standardsskill as the canonical source for design claims. Load the matching references; do not copy the standards into this skill or artifact. - Project docs:
AGENTS.md,README.md,CONTEXT.md, architecture docs, ADRs, verification config, current VCS state, and relevant existing plans.
The artifact rules in this skill are canonical. For source patterns and examples, read the vendored HumanLayer v2 planning skills at reference/humanlayer-riptide-v2-skills/ and the improve-codebase-architecture skill when architecture/deepening vocabulary matters.
Stage Contract
Default to the smallest stage that creates durable progress.
| Stage | Use when | Inputs | Output | Stop gate |
|---|---|---|---|---|
| Research questions | The current-state unknowns are broad or ambiguous | Roadmap item, plan, user request | Questions about how the system works today | Stop after questions; ask whether to research |
| Research | Questions exist and current behavior must be established before design | Research questions or explicit scope | Descriptive current-state research | Stop after research; recommend design discussion |
| Design discussion | A feature or architecture direction needs judgment | Source item plus research or enough repo context | Options, recommendation, decisions, open questions | Stop for review; do not outline yet |
| Structure outline | The design is accepted or has one clearly recommended direction | Accepted/current design discussion | Vertical implementation slices | Stop for review; do not write final plan yet |
| Final plan | The outline is accepted or equivalent structure is provided | Accepted/current outline | Executor-safe implementation plan | Stop for execution handoff |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 170 lines · 73 tokens per session scan A 994bf431a40c
feature-planning-artifacts is a skill published in the GitHub repository joshuadavidthomas/agent-skills (49 stars, last pushed 1mo ago), licensed MIT. It adds 73 tokens to every session and 2,550 once invoked, about $0.0004 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 2026-08-30.
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