Case Summary
Produces an attorney-ready memo from a corpus of legal documents supplied by the user. Use when a user shows up with a folder, zip, or vault of case documents and asks for a case summary, case evaluation, litigation package, intake memo, matter overview, or "can you summarize this case for me." The skill ingests the corpus into a searchable index, OCRs anything non-searchable, inventories and diagnoses the practice area, loads the appropriate practice-area playbook module(s) (PI/tort, commercial litigation, IP infringement, or user-authored extensions), iteratively searches the corpus across eight core dimensions plus any module-specific dimensions, defers specialized document clusters (depositions, medical records, discovery, liens) to dedicated sibling skills, and synthesizes a cited memo.
Case Summary
A user arrives with a pile of legal documents — often hundreds or thousands — and asks for a summary. This skill is the playbook for doing that well, across any practice area.
The work is map-reduce: map the corpus across the dimensions that matter, reduce the hits into a memo. The skill does not prescribe a specific search tool — it describes the work. references/BACKENDS.md lists concrete implementations the agent can use today.
The core describes what every case has (parties, timeline, evidence, claims, exposure, defenses, procedural status, red flags). Practice-area playbooks (references/PLAYBOOK-*.md) specialize the core for specific domains. Specialized document types (depositions, medicals, discovery, liens) route out to dedicated sibling skills per references/ROUTING.md.
Related skills
case-chronology— when the deliverable is a dated timeline rather than a full memocase-intake-initial-fact-memo— for commercial-litigation intake memoscase-viability-report— for go/no-go screening before accepting a matterpi-demand-summary— when the objective is a PI settlement package, not a case evaluationdemand-letter— when the objective is a pre-suit demand letterdeposition-summary— for deposition transcripts; route perROUTING.mddiscovery-summary— for interrogatory/RFP/RFA responses; route perROUTING.mdmedical-record-chronology— for dense medical-records sets; route perROUTING.mdmedical-treatment-summary— for causation-focused treatment narrativesevidence-liability-summary— for plaintiff-side liability element breakdownslien-resolution-summary— for post-settlement lien trackinglegal-strategy-summary— for motion-and-discovery roadmap deliverablessettlement-summarization— for post-memo settlement activity
Checkpoint A: pre-ingest intake (mandatory)
Ask every time unless the user says "use defaults" or "just go." Gather:
- Practice area guess — PI, commercial, IP, regulatory, criminal, family, bankruptcy, etc. The agent can update this after Inventory, but a guess narrows the initial playbook loader.
- Expected document types — pleadings, discovery, depositions, medicals, contracts, corporate records.
- Custodians / sources — who produced the files, and in what posture (client production, opposing-counsel production, third-party subpoena).
- Date range — anchor the timeline.
- User objective — evaluation memo, viability screen, demand prep, settlement prep, strategy roadmap. Different objectives trigger different sibling skills per
ROUTING.md. - Privilege posture — work-product only, attorney-client privileged, or litigation-ready.
- Venue / jurisdiction — affects SOL, statutory-notice requirements, governing law.
Defaults (if the user doesn't answer): PI/tort playbook; evaluation memo; attorney work-product; U.S. state-court posture. Label every default explicitly in the memo header.
The loop
1. Ingest. Put the corpus into something searchable. See references/WORKFLOW.md for the phase description and references/BACKENDS.md for implementations.
2. OCR. Any PDF that isn't already searchable will not be indexed usefully. Handle OCR before searching on files that need it. Asynchronous — keep moving.
3. Inventory. Pull the object list. Skim filenames to build a mental model: what practice area, what kinds of documents, how many of each. This is the only time the agent cares about every file.
4. Diagnose practice area. From the inventory plus a single global-overview query, pick one or more playbook modules from references/PLAYBOOK-*.md. Each has triggers in its frontmatter that match filenames and content signals. Record the choice in the memo header. When no module fits, proceed core-only and note it.
5. Map — iterative search per dimension. For each of the eight core dimensions in references/CORE-DIMENSIONS.md:
- Run the base queries from
references/SEARCH-PLAYBOOK.md. - Run the module queries from each loaded playbook for that dimension.
- Read the top 3–10 chunks per query. Cite everything the memo will rely on by object name + page.
- Where the corpus contains specialized document clusters (≥1 full deposition, dense medical records set, discovery responses, lien correspondence), delegate per
references/ROUTING.mdand consume the sibling skill's output rather than summarizing inline.
Don't brute-force read every file. Drive the search with focused queries, pull the 3–10 most relevant chunks per query, follow up when hits are load-bearing, route when a cluster warrants a sibling skill.
6. Reduce — synthesize. Assemble the memo using references/OUTPUT-TEMPLATE.md's core skeleton, plus the output sections contributed by each loaded playbook. Every claim cites an object + page (or chunk ID). No citation = cut or label as assumption.
7. Review. Run the quality checklist below (core items + playbook-specific items). Flag any unsatisfied items.
Checkpoint B: post-memo alignment (mandatory)
After delivering the draft, ask:
- Did the right playbook module(s) get loaded? (List them.)
- Which sibling skills were invoked, and did their outputs get integrated correctly?
- Are there coverage gaps — dimensions the agent couldn't populate from the corpus?
- Any claims in the memo that depend on unverified legal citations flagged
[VERIFY]? - Is attorney review explicitly required before any downstream use?
If the user doesn't answer, default to: list the loaded playbooks and invoked siblings; flag any dimension that returned "no evidence found"; require attorney review.
What this skill does not do
- It does not value the case. Ranges belong in the memo when a loaded playbook supplies the methodology, but the skill doesn't substitute for attorney judgment about jurisdiction, venue, or negotiation posture.
- It does not resolve liens, draft pleadings, or send demands. It identifies them and routes to the sibling skill that does.
- It does not replace an attorney review of the final memo. Always label the memo AI-generated and require sign-off.
Scale notes
- < 20 files: skip the search loop; read every document directly. See
references/BACKENDS.mdsmall-corpus recipe. - 20–200 files: one pass through the search playbook, one memo. ~1 hour.
- 200–2,000 files: expect 40–80 targeted searches across the dimensions, checkpoint notes as the agent goes. Multi-hour run.
- 2,000+ files: expect 100+ targeted queries; tighten scoping with module-specific filters and entity-mode searches; budget multi-hour run time. One corpus — the agent works it harder, not by fragmenting it.
Core quality checklist
Every matter:
- [ ] Every file is either searched-over or explicitly noted as out-of-scope
- [ ] Every OCR job finished (or its absence is noted in the memo)
- [ ] Parties, venue, posture correct with citations
- [ ] Timeline continuous; gaps >30 days flagged
- [ ] Each claim element has at least one evidentiary citation or explicit gap note
- [ ] Each asserted defense has supporting-evidence citation or a "pled without support" note
- [ ] Exposure/remedies section shows methodology, not an attorney valuation
- [ ] Red flags section is honest, not decorative — each item names a next action
- [ ] Every claim in the memo traces to an object + page or is labeled an assumption
- [ ] Unverified statutes/rules/cases marked
[VERIFY] - [ ] Memo labeled AI-generated, requires attorney review
Plus every playbook-specific item from each loaded PLAYBOOK-*.md's Quality checklist section.
Troubleshooting
- OCR didn't run on a file. The file isn't searchable. Record the file in the memo's out-of-scope list, try a different OCR engine if the backend supports one, or ask the user to re-upload a text-searchable version.
- Search returns noise, not relevant hits. Run a global-overview query first to discover the vocabulary the documents use; re-issue targeted queries using that vocabulary. Narrow with keyword anchors (party names, dates, case numbers) once known.
- Practice area ambiguous; no playbook fits cleanly. Proceed core-only (core dimensions +
SEARCH-PLAYBOOK.mdbase queries). Note the ambiguity inVIII Strengths / Weaknesses / Red Flags. Offer the user a recommendation to narrow. - Wrong playbook picked. Re-enter step 4 (Diagnose practice area) with the new information. Load the correct module; keep hits from the previous pass that still apply.
- Corpus too large for a single pass. Prioritize the dimensions that matter for the user's stated objective. Run a triage pass (parties, posture, top 3 claims, headline exposure) first, then expand to full coverage if time allows. Surface to the user which dimensions are deep vs. triage in the memo header.
- Sibling skill unavailable or returns nothing useful. Note it in the memo header (
Sibling skills invoked), record the cluster the agent wanted to route, and summarize the cluster inline with reduced depth. Attorney review should consider whether a focused sibling-skill run is warranted before the memo is used downstream. - Multi-matter corpus (the folder mixes unrelated cases). Surface to the user before proceeding. The skill summarizes one matter at a time; don't silently merge.
No additional documents ship with this skill.
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