Imported from borghei/claude-skills (
research/dossier/SKILL.md). Install upstream withnpx skills add borghei/claude-skills --skill dossier. Copyright stays with the author (MIT + Commons Clause).
Intelligence Dossier
A research skill for producing structured intelligence dossiers — the kind of document a CEO reads before a meeting, a PM reads before market-entry, or an investor reads before due diligence.
When to use this skill
- Deal-prep dossier before a major partnership / acquisition meeting
- Executive briefing ahead of a board, customer, or regulator meeting
- Market-entry analysis for a new geography or vertical
- Due-diligence overview for investment or M&A consideration
- Competitor profile in depth
- Person dossier ahead of executive recruiting or board engagement
Inputs the advisor expects
- Subject (company / person / market / domain)
- Purpose (deal-prep, due diligence, briefing — affects depth + emphasis)
- Audience (exec, board, working team)
- Timeline / deadline
- Known starting sources
- Sensitive areas to dig into
Clarify First
Before building the dossier, settle the inputs below. When one is missing or vague and would change the result, ask about it; when it wouldn't, use a sensible default and say which one you used.
- Subject + subject type (company / person / market): selects the outline template and which sections apply.
- Purpose (deal-prep, due diligence, briefing, market-entry): drives depth, emphasis, and the Implications section.
- Audience (exec, board, working team): sets altitude and length of the executive summary.
- Key decision or risk to inform: drives the Risks + Open Questions and Recommendations sections.
Ask about the two or three inputs that matter most for this request, not the whole list. If the user wants a result straight away, produce it and state your assumptions at the top.
Workflows
Workflow 1 — Generate dossier outline
- Specify subject type + purpose.
- Run
dossier_outline_generator.pyto produce a structured outline tailored to subject + purpose. - Assign owners + research targets per section.
python3 dossier/scripts/dossier_outline_generator.py \
--subject-type company --purpose deal-prep --format markdown
Workflow 2 — Validate source triangulation
- Capture claims with supporting sources.
- Run
source_triangulation_validator.pyto check each claim has multiple independent supporting sources + source reliability. - Flag thinly-sourced claims for additional research.
python3 dossier/scripts/source_triangulation_validator.py \
--input claims_with_sources.json --format markdown
Workflow 3 — Separate facts from inferences
- Capture dossier statements.
- Run
fact_inference_separator.pyto classify each statement and flag unsupported inferences.
python3 dossier/scripts/fact_inference_separator.py \
--input dossier_statements.json --format markdown
Decision frameworks
The dossier hierarchy
A useful structure for any dossier:
- Executive summary (1 page, lead with takeaway)
- Subject overview (facts: what they are)
- Context (market, history, environment)
- Capabilities + assets (what they can do)
- People + leadership (who runs it)
- Performance + trajectory (numbers, trends)
- Relationships + ecosystem (who they're with)
- Risks + open questions (what we don't know)
- Implications + recommendations (so what)
- Sources + methodology (how we know)
Fact vs inference discipline
Three categories per statement:
| Category | Definition | Example |
|---|---|---|
| Fact | Verifiable, sourced | "Founded 2018; HQ in Chicago" |
| Inference | Reasoned from facts | "Likely targeting enterprise segment based on hiring pattern" |
| Speculation | No supporting evidence | "Might pivot to AI next year" |
A trustworthy dossier separates these clearly. Mixing them = loss of credibility.
Source reliability scoring (Admiralty Code adapted)
| Reliability | Code | Description |
|---|---|---|
| Completely reliable | A | Established, history of completely reliable info |
| Usually reliable | B | History of mostly reliable info |
| Fairly reliable | C | History of reliable info with notable errors |
| Not usually reliable | D | Limited history; mixed accuracy |
| Unreliable | E | Known for inaccurate info |
| Cannot be judged | F | New / unknown source |
| Information credibility | Code | Description |
|---|---|---|
| Confirmed | 1 | Confirmed by other independent sources |
| Probably true | 2 | Not confirmed; consistent with other info |
| Possibly true | 3 | Not confirmed; reasonable but unsupported |
| Doubtful | 4 | Inconsistent with other info |
| Improbable | 5 | Contradicted by other info |
| Cannot be judged | 6 | New info; no validation possible |
A "B-2" rated claim is "usually reliable source, probably true" — workable. An "F-6" claim is "unknown source, unverified" — barely worth including.
Triangulation principle
For each significant claim:
- 1 source: anecdotal; flag explicitly
- 2 independent sources: workable (most dossier claims should reach this)
- 3+ independent sources: confirmed; safe to assert
"Independent" means not derived from the same underlying source. Two news articles citing the same press release ≠ 2 independent sources.
Common engagements
"Build a dossier on company X before our acquisition meeting"
- Run outline generator (subject=company, purpose=deal-prep).
- Pull: financials, leadership, products, customers, IP, tech stack, regulatory posture.
- Identify red flags: undisclosed litigation, key person dependencies, customer concentration, regulatory risk.
- Recommendations: questions to ask in meeting; deal structure implications.
"Executive briefing for senator's office meeting"
- Run outline (subject=person/organization, purpose=briefing).
- Pull: voting record, recent statements, committee assignments, donor profile, alignment with our position.
- Anticipate likely questions; prepare positions.
"Market-entry analysis for [country]"
- Run outline (subject=market, purpose=market-entry).
- Pull: market size, growth, competitive landscape, regulatory, distribution, cultural / business norms, talent.
- Compare entry options (direct, partner, acquisition).
Anti-patterns to avoid
- Mixing facts + inferences without labels. Reader can't calibrate trust.
- Single-source claims presented as confirmed. Anecdote dressed as data.
- Unsourced "everyone knows" claims. Often turn out wrong.
- Padding with low-relevance facts. Bloated dossier loses signal.
- Burying risks at the end. Risks should be surfaced upfront.
- No update mechanism. Stale dossier on important subject = bad decisions.
- Adversarial language about subject. Bias erodes credibility.
Scope & Limitations
In Scope:
- Dossier outlines tailored to subject type (company, person, market) and purpose (deal-prep, due diligence, briefing, market entry) with
dossier_outline_generator.py - Source triangulation checks with
source_triangulation_validator.py: single-source claims, low-reliability sources and sources that are not independent - Fact, inference and speculation labelling with
fact_inference_separator.py, flagging unsupported inferences and over-confident speculation - The ten-part dossier hierarchy and source rating with an adapted Admiralty Code
Out of Scope:
- Collecting the information. The skill structures and checks research the user gathers.
- Academic literature search (see
research/litreview/) - Legal due diligence and legal risk opinions (see
c-level-advisor/general-counsel-advisor/) - Competitor teardowns for positioning and sales use (see
business-growth/competitive-teardown/)
Important Caveats:
- The tools do not search the web or any database. Claims, sources, reliability codes and independence links are all entered by the user.
- Source independence is only as accurate as the
independent_fromlinks supplied. Two articles that repeat one press release count as independent unless the user marks them. - Classification of statements uses the declared category, the evidence attached and wording patterns. It is a check, not a verification of the facts.
- A dossier is a snapshot. Facts about companies, people and markets go stale and need a set review date.
References
references/dossier-frameworks-and-structure.md— outline patterns per subject typereferences/source-triangulation-and-reliability.md— source assessment, triangulationreferences/fact-vs-inference-discipline.md— categorization + writing patterns
Related skills
research/litreview— academic literature searchc-level-advisor/ceo-advisor— strategic briefing patternsc-level-advisor/general-counsel-advisor— legal due diligence overlapbusiness-growth/competitive-teardown— competitive intel anglebusiness-growth/customer-success-manager— account research patterns
