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, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• 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

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Workflows

Workflow 1 — Generate dossier outline

1. Specify subject type + purpose.
2. Run dossier_outline_generator.py to produce a structured outline tailored to subject + purpose.
3. 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

1. Capture claims with supporting sources.
2. Run source_triangulation_validator.py to check each claim has multiple independent supporting sources + source reliability.
3. 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

1. Capture dossier statements.
2. Run fact_inference_separator.py to 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:

1. Executive summary (1 page, lead with takeaway)
2. Subject overview (facts: what they are)
3. Context (market, history, environment)
4. Capabilities + assets (what they can do)
5. People + leadership (who runs it)
6. Performance + trajectory (numbers, trends)
7. Relationships + ecosystem (who they're with)
8. Risks + open questions (what we don't know)
9. Implications + recommendations (so what)
10. Sources + methodology (how we know)

Fact vs inference discipline

Three categories per statement:

A trustworthy dossier separates these clearly. Mixing them = loss of credibility.

Source reliability scoring (Admiralty Code adapted)

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"

1. Run outline generator (subject=company, purpose=deal-prep).
2. Pull: financials, leadership, products, customers, IP, tech stack, regulatory posture.
3. Identify red flags: undisclosed litigation, key person dependencies, customer concentration, regulatory risk.
4. Recommendations: questions to ask in meeting; deal structure implications.

"Executive briefing for senator's office meeting"

1. Run outline (subject=person/organization, purpose=briefing).
2. Pull: voting record, recent statements, committee assignments, donor profile, alignment with our position.
3. Anticipate likely questions; prepare positions.

"Market-entry analysis for [country]"

1. Run outline (subject=market, purpose=market-entry).
2. Pull: market size, growth, competitive landscape, regulatory, distribution, cultural / business norms, talent.
3. 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.

References

• references/dossier-frameworks-and-structure.md — outline patterns per subject type
• references/source-triangulation-and-reliability.md — source assessment, triangulation
• references/fact-vs-inference-discipline.md — categorization + writing patterns

Related skills

• research/litreview — academic literature search
• c-level-advisor/ceo-advisor — strategic briefing patterns
• c-level-advisor/general-counsel-advisor — legal due diligence overlap
• marketing/competitive-teardown — competitive intel angle
• business-growth/customer-success-manager — account research patterns