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 prismgit 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/prism)<a href="https://agentmods.dev/skills/outlinedriven/odin-claude-plugin/prism"><img src="https://agentmods.dev/badge/skills/outlinedriven/odin-claude-plugin/prism/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/prism"><img src="https://agentmods.dev/badge/skills/outlinedriven/odin-claude-plugin/prism.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 | $0.00040 | $0.01897 |
| Opus 5 | $0.00020 | $0.00949 |
| Sonnet 5 | $0.00008 | $0.00379 |
| Haiku 4.5 | $0.00004 | $0.00190 |
Grade A, and why
prism 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 2d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prism
Contract
| Field | Bound contract |
|---|---|
| Trigger | One reviewer angle is insufficient, the user asks to "prism this" or review from different angles, one read may be an artifact of how the question was framed, or the user suspects the current direction of work is tunnel-visioned or inherited its framing. |
| Authority | Read-only. No writes; nothing to roll back. No remote mutation. |
| Side effect | A divergence-first report in chat only; create or change no files; bounded fresh zero-context sub-reads are spawned only as inputs to classification. |
| Done | Bait is stripped from the target; every read carries exactly one classification label (artifact mode: divergent-incompatible, divergent-compatible, convergent; direction mode adds ambiguous); shared-root clustering is complete; cluster order follows the mode, with direction mode listing ambiguous clusters first; convergence is labeled reassurance with no consensus wording; one decisive resolving question is stated. |
Inputs
- Mode: artifact or direction; default artifact. Direction applies when the user asks whether a current direction of work (plan, approach, or framing) is tunnel-visioned or inherited its framing; artifact applies when a concrete artifact is reviewed.
- Target: the artifact to review, or the direction of work to stress-test. Required.
- Lenses or viewpoints: review lenses for artifact mode; distinct viewpoints for direction mode (opposing assumption, adjacent domain, historical failure mode, resource constraint, user-population segment). Optional; if omitted, derive them from the target's genuinely distinct failure modes.
- Context: background material that may inform the reads but must not constrain them to a single frame. Optional.
- Decision: a decision the review must inform. Optional.
- Read count: between 2 and 5; default 3. Optional. The same model is allowed across reads: this checks framing blind spots, not cross-model truth.
Procedure
- Read the target end to end before selecting lenses. In direction mode the target is the direction statement; read it with its surrounding context. Treat supplied context as evidence only when it is available and attributable; do not invent missing facts. Done when: the target is read completely and no fact is invented.
- Select two to five lenses, each representing a distinct failure mode. Mode artifact: merge proposed lenses that test the same failure mode; let the artifact determine the count rather than defaulting to a fixed number. Mode direction: pick distinct viewpoints such as opposing assumption, adjacent domain, historical failure mode, resource constraint, or user-population segment; no read may copy or restate another. Done when: each lens targets a distinct failure mode and duplicates are merged.
- Strip the framing. Remove the session's own examples, suggested answers, preferred naming, and framing-specific wording down to the underlying goal, constraints, and known facts. Mode artifact: restate the bare review question in neutral terms that do not carry the session's loaded vocabulary; if a term is load-bearing, keep its denotation but drop the framing that points at one answer. Mode direction: strip bait from the direction statement, removing leading, suggestive, and conclusory language; restate what is being attempted and why, preserving the decision's substance without its rhetorical frame. Done when: the bare question or direction statement is restated in neutral terms with loaded framing or bait removed.
- Fan out 2 to 5 fresh zero-context reads of the stripped question or direction, default 3, each evaluated independently through one lens. The same model is allowed. Done when: 2 to 5 fresh reads are dispatched, each through a distinct lens.
- Normalize verdicts. For each lens give exactly one verdict (
pass,fail, orunclear) and the single most load-bearing reason supported by the target or supplied context. Do not average or flatten conflicting verdicts. Done when: every lens has one verdict and one load-bearing reason. - Classify each perspective. Assign exactly one label:
divergent-incompatible(challenges a premise the direction depends on, or identifies a framing flaw, hidden assumption, or outcome that contradicts the intent),divergent-compatible(adds, reframes, or proposes a meaningfully different path or emphasis without discarding the direction),convergent(independently arrives at the same framing or verdict), orambiguous(cannot be classified with confidence; include a one-sentence explanation). Do not force-fit a label. Done when: every perspective carries exactly one classification label. - Cluster by shared root before reporting. Group reads that share the same underlying assumption, evidence source, or structural concern; name the root and put the instances under it as evidence. Reads with no shared root form single-member clusters. Done when: every read is assigned to a cluster with its root labeled.
- Report divergence-first. Mode artifact: incompatible divergence, then compatible divergence, then convergence. Mode direction: ambiguous clusters first, then incompatible, then compatible, then convergent; within each cluster, order by relevance to the core claim. Label convergence as reassurance, never proof; in direction mode note that convergent reads confirm the framing was inherited, not chosen. Use no consensus, agreement, majority, or weight wording when describing the reads collectively; if such wording appears, rewrite the sentence with per-read or per-cluster attribution. No majority vote, no averaging, no "verified." Done when: the report is emitted in the mode's order with convergence labeled as reassurance and no consensus wording present.
- Name one decisive resolving question whose answer would resolve the deepest disagreement. For full convergence, state the shared verdict and mark the resolving question as
none (no lens conflict). Done when: the decisive question is stated, ornone (no lens conflict)with the shared verdict. - Check that every selected lens appears once, every verdict has evidence, every perspective is classified, and the grouping follows from the verdicts. Return the report only in chat. Done when: every lens appears once, every verdict has evidence, every perspective is classified, and the grouping follows from the verdicts.
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.
- 2d ago First seen · 65 lines · 40 tokens per session scan A fa9fd34f4dd0
prism is a skill published in the GitHub repository OutlineDriven/odin-claude-plugin (35 stars, last pushed yesterday), licensed Apache-2.0. It adds 40 tokens to every session and 1,897 once invoked, about $0.0002 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 2026-09-06.
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