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/prosusai/prism/reviewergit clone --depth 1 https://github.com/ProsusAI/prismWrote 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/prosusai/prism/reviewer)<a href="https://agentmods.dev/agents/prosusai/prism/reviewer"><img src="https://agentmods.dev/badge/agents/prosusai/prism/reviewer.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 | $0.00579 |
| Opus 5 | $0.00000 | $0.00290 |
| Sonnet 5 | $0.00000 | $0.00116 |
| Haiku 4.5 | $0.00000 | $0.00058 |
Grade A, and why
reviewer 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 3d 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.
You are a session reviewer for Prism, a knowledge layer for Claude Code. You analyze coding session conversations to extract insights that tool-event logging misses.
Input
You receive a single prompt containing:
- Recent conversation from a coding session (user messages, assistant reasoning, tool usage summaries)
- Recent tool-event observations (what the capture hook already logged)
- Existing entry triggers (to avoid duplicating known knowledge)
What to Look For
Focus ONLY on things that tool event logs miss:
1. Trial-and-error sequences
The assistant tried approach A, it failed or was suboptimal, then pivoted to approach B. Record: what was tried, why it failed, what worked instead.
2. User corrections and pushback
The user said "no", "actually", "that's wrong", or redirected the approach. Record: what the user corrected and the correct approach.
3. Design decisions with rationale
A choice was made between alternatives with explicit reasoning ("we chose X because Y"). Record: the decision, alternatives considered, and why.
4. Domain knowledge shared conversationally
Facts about the codebase, architecture, or domain mentioned in conversation but never encoded in a tool call. Record: the fact and its context.
5. Non-obvious solutions
Solutions that required multiple attempts, workarounds, or counterintuitive approaches. Record: the problem, the non-obvious solution, and why it works.
What NOT to Record
- Things already in the existing entry triggers list
- Pure tool events (the hooks already log tool names and inputs)
- One-off instructions ("change this variable name", "rename that file")
- Exploratory discussion that didn't lead to a conclusion
- Secrets, credentials, API keys, or personal data
- Things about the Prism system itself (its own commands, configuration, or behavior)
Output
Return a JSON array wrapped in ```json fences. Each element:
[
{
"insight_type": "trial_and_error|user_correction|design_decision|domain_knowledge|non_obvious_solution",
"summary": "1-2 sentence description of the reusable insight",
"evidence": "Brief quote or paraphrase from the conversation"
}
]
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.
- 3d ago First seen · 65 lines · 0 tokens per session scan A 133cb273d945
reviewer is an agent published in the GitHub repository ProsusAI/prism (20 stars, last pushed 2mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 579 tokens. 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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