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 OutlineDriven/odin-claude-plugin --skill skill-progressive-disclosure-designgit clone --depth 1 https://github.com/OutlineDriven/odin-claude-pluginWrote 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/outlinedriven/odin-claude-plugin/skill-progressive-disclosure-design)<a href="https://agentmods.dev/skills/outlinedriven/odin-claude-plugin/skill-progressive-disclosure-design"><img src="https://agentmods.dev/badge/skills/outlinedriven/odin-claude-plugin/skill-progressive-disclosure-design/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/outlinedriven/odin-claude-plugin/skill-progressive-disclosure-design"><img src="https://agentmods.dev/badge/skills/outlinedriven/odin-claude-plugin/skill-progressive-disclosure-design.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 | $0.00068 | $0.02290 |
| Opus 5.5 | $0.00027 | $0.00916 |
| Sonnet 5.5 | $0.00014 | $0.00458 |
| Haiku 4.5 | $0.00007 | $0.00229 |
Grade A, and why
skill-progressive-disclosure-design 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 1mo 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill progressive disclosure design
Contract
| Field | Bound contract |
|---|---|
| Trigger | the model is creating or refactoring a skill, faces a SKILL.md over 300-400 lines, or confuses triggering with disclosure |
| Authority | reversible-local: write only named local skill files; rollback by restoring prior file contents |
| Side effect | restructures the skill's files (split or monolith with reference pointers), limited to the target skill directory |
| Done | justified split-or-monolith decision with pointer hygiene and an architecture-eval plan |
Inputs
- The existing skill directory (
SKILL.md, anyreferences/,scripts/). Required. - The skill's YAML description. Required for triggering diagnosis.
- Empirical evidence (eval transcripts, token counts) if available. Optional; absence triggers the instrumentation recommendation path.
Procedure
-
Diagnose triggering vs. disclosure. Separate these two problems before deciding whether to split.
- Triggering is whether the model invokes the skill at all. Driven entirely by the YAML description. File splitting does not affect triggering. If the question is "my skill doesn't trigger reliably", do not split files. Fix the description.
- Progressive disclosure is what loads after the skill activates.
SKILL.mdbody always loads.references/*only loads whenSKILL.mdtells the model to read a specific file.scripts/*executes without loading into context. This is where context protection happens. - If the user asks about splitting because of triggering issues, surface the confusion first and redirect. Do not recommend structural changes until the triggering question is resolved. Done when: the problem is classified as triggering, disclosure, or both, and the user understands the distinction.
-
Default: do not split. A monolithic
SKILL.mdbeats a split one until proven otherwise. Split only when at least one holds:SKILL.mdexceeds ~400 lines and content has natural branches.- Empirical evidence (eval transcripts) shows the model wasting context on irrelevant sections.
- Specific content is large and only needed in narrow conditions.
- Record the rationale for the monolith-or-split decision before proceeding.
- Monolith pros: single context load, no router prose, no wrong-load risk, one source of truth, easier human review.
- Monolith cons: every invocation pays full token cost, does not scale past ~500 lines, no mechanism to gate rare content. Done when: the default is stated and the specific conditions that would override it are recorded.
What ships with it
1 file 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.
- 1mo ago First seen · 117 lines · 68 tokens per session scan A 7c417245f72a
skill-progressive-disclosure-design is a skill published in the GitHub repository OutlineDriven/odin-claude-plugin (39 stars, last pushed 27d ago), licensed Apache-2.0. It adds 68 tokens to every session and 2,290 once invoked, about $0.0003 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 2026-09-04.
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