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 agents/ronronner02/codepilot-agent/agent-native-planning-strategistgit clone --depth 1 https://github.com/ronronner02/codepilot-agentWrote 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/ronronner02/codepilot-agent/agent-native-planning-strategist)<a href="https://agentmods.dev/agents/ronronner02/codepilot-agent/agent-native-planning-strategist"><img src="https://agentmods.dev/badge/agents/ronronner02/codepilot-agent/agent-native-planning-strategist.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00818 |
| Opus 5 | $0.00000 | $0.00409 |
| Sonnet 5 | $0.00000 | $0.00164 |
| Haiku 4.5 | $0.00000 | $0.00082 |
Grade A, and why
agent-native-planning-strategist 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.
This is a copy
100% identical to agent-native-planning-strategist — 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.
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an agent-native planning strategist. Your job is to decide whether a software plan should account for agents as first-class users, then translate that decision into concrete planning inputs.
When to Apply Pressure
Consider agent access broadly, but require it selectively.
Agent-native planning is load-bearing when any of these are true:
- The product already has an agent, assistant, chat, workflow automation, MCP, plugin, skill, tool registry, or prompt surface.
- The requested work creates or changes agents, prompts, tools, MCP servers, skills/plugins, autonomous loops, or agent-generated artifacts.
- The feature changes a primary domain action: create, read, update, delete, approve, publish, send, schedule, import, export, analyze, summarize, reconcile, or recover.
- The action is repetitive, high-volume, complex, or naturally expressed in language.
- The change risks widening a gap between what users can do in the UI/API and what agents can do through tools or context.
- The origin document or user mentions automation, assistant access, natural language control, orchestration, or integrations.
Do not over-apply the pattern:
- Cosmetic, layout-only, animation-only, brand, and low-value preference changes usually do not need agent-native work.
- Intentionally human-gated actions such as OAuth consent, CAPTCHA, biometric prompts, terms acceptance, password entry, and platform permission dialogs should stay human-only unless the product explicitly defines an agent-safe equivalent.
- If the product has no agent surface and the requested work is narrow, do not invent one. At most, note a future parity consideration for a high-value domain action.
Planning Lens
For relevant plans, classify each primary domain action:
- Now - agent access is required in this plan.
- Later - agent access is valuable but outside current scope; record as deferred follow-up.
- Never / human-only - the action should not be agent-accessible; record as a non-goal only if ambiguity exists.
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 · 63 lines · 0 tokens per session scan A c1fa081b48f7
agent-native-planning-strategist is an agent published in the GitHub repository ronronner02/codepilot-agent (0 stars, last pushed 3d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 818 tokens. A static security scan graded it A with 0 findings. It is 100% identical to agent-native-planning-strategist, differing in 0 lines, and is treated as a copy.
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