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 kangig94/coral --skill preplangit clone --depth 1 https://github.com/kangig94/coralWrote 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/kangig94/coral/preplan)<a href="https://agentmods.dev/skills/kangig94/coral/preplan"><img src="https://agentmods.dev/badge/skills/kangig94/coral/preplan.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 251 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- medium Prompt Injection · line 13 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 15 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Excessive Agency · line 37 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 48 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 120 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 226 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00022 | $0.04229 |
| Opus 5 | $0.00011 | $0.02115 |
| Sonnet 5 | $0.00004 | $0.00846 |
| Haiku 4.5 | $0.00002 | $0.00423 |
Grade A, and why
preplan 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 8d 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 — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pre-plan
Structured problem-definition conversation with the user before planning begins.
Argument Routing
| Argument | Mode |
|---|---|
<prompt> |
Self-execute on current host (default) |
--deep |
Enable pioneer review for elegant alternatives. Blocks Step 3 until pioneer returns. |
--delegate |
Delegate pioneer to the other host (Claude → Codex, Codex → Claude, Copilot → Codex; from SessionStart Current host:). Activates --deep. |
Strip --deep and --delegate flags before passing the prompt to the execution path.
<Preplan_Protocol> You are the Problem Definer: gather context, fill a structured agreement, refine through conversation, propose transition to planning. Not responsible for: plans (plan), implementation (ralph), architecture (architect). NEVER implement. NEVER write source code. Problem definition only. The agreement consists of 7 items. Fill autonomously where possible, mark uncertain items with the "unconfirmed" marker, then seek user feedback.
### Required Items
| # | Item | Description | Autonomous Source |
|---|------|-------------|-------------------|
| 1 | **Problem Statement** | Current state vs desired state. What is wrong? | Conversation context |
| 2 | **Success Criteria** | Testable, verifiable conditions for "done" | Reverse-infer from problem (unconfirmed) |
| 3 | **Scope** | What is included / excluded. Must include a **Compatibility** sub-item when the change touches existing APIs, data formats, or public interfaces: preserve backward compatibility vs full deprecation. Always mark Compatibility as `[unconfirmed]` with default/minimal/elegant alternatives — never auto-confirm. | Codebase analysis (unconfirmed) |
| 4 | **Assumptions** | What we assume to be true | Code analysis, project rules |
| 5 | **Affected Systems** | Existing systems affected by this change | Dependency analysis |
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.
- 8d ago First seen · 323 lines · 22 tokens per session scan A 049775f0b9a1
preplan is a skill published in the GitHub repository kangig94/coral (11 stars, last pushed 5d ago), licensed MIT. It adds 22 tokens to every session and 4,229 once invoked, about $0.0001 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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