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 odin33g/family-court-strategist --skill evidence-reviewgit clone --depth 1 https://github.com/odin33g/family-court-strategistWrote 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/odin33g/family-court-strategist/evidence-review)<a href="https://agentmods.dev/skills/odin33g/family-court-strategist/evidence-review"><img src="https://agentmods.dev/badge/skills/odin33g/family-court-strategist/evidence-review/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/odin33g/family-court-strategist/evidence-review"><img src="https://agentmods.dev/badge/skills/odin33g/family-court-strategist/evidence-review.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00076 | $0.00759 |
| Opus 5 | $0.00038 | $0.00380 |
| Sonnet 5 | $0.00015 | $0.00152 |
| Haiku 4.5 | $0.00008 | $0.00076 |
Grade A, and why
evidence-review 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 12d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evidence Review
Perform a comprehensive cross-document analysis of the user's case vault. This is where individual document analyses get connected into case-level insights.
What to Do
1. Read the Vault
Read the key structural files first:
- CASE-DETAILS.md (case basics)
- MASTER-TIMELINE.md (chronology)
- EVIDENCE-MATRIX.md (current evidence map)
- CROSS-DOCUMENT-ANALYSIS.md (existing contradictions)
Then read individual document analyses in legal-documents/ and communications/.
2. Cross-Document Analysis
Run every document against every other document looking for:
Timeline Conflicts — Same event described with different dates or sequences across documents. Create a table showing Document A vs Document B.
Statement Evolution — How someone's story changes over time. Track specific claims from affidavit → report interview → court hearing. Changes in detail, emphasis, or framing are significant.
Professional Opinion Conflicts — Where experts, caseworkers, or other professionals disagree. Which opinion is better supported by independent evidence?
Internal Contradictions — Where a single document contradicts itself. Note both statements with paragraph references.
Credibility Vulnerabilities — Specific points where a party's credibility can be challenged. Build a list with evidence links.
3. Pattern Detection
Look across all evidence for:
- Contact blocking or avoidance patterns (track frequency, excuses, timing)
- Alienation indicators (child's language, loyalty conflicts, rejection without cause)
- Allegation timing (do new allegations appear before court dates?)
- System failures (recommendations not followed, assessments incomplete)
- Communication patterns (response rates, tone shifts, silence periods)
For each pattern: how many instances? How strong is the evidence? What would a court find compelling?
4. Gap Analysis
Identify what's MISSING:
- Documents that should exist but aren't in the vault
- People who should have been assessed but weren't
- Questions that should have been asked but weren't
- Records that could be subpoenaed
- Evidence that would strengthen weak claims
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.
- 12d ago First seen · 87 lines · 76 tokens per session scan A 57546915b1f2
evidence-review is a skill published in the GitHub repository odin33g/family-court-strategist (17 stars, last pushed 5d ago), licensed MIT. It adds 76 tokens to every session and 759 once invoked, about $0.0004 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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