Agent skill

Dossier

by borghei in borghei/Claude-Skills

Structured intelligence dossiers on companies, people, markets, or domains, with source triangulation and fact/inference discipline.

MITAuto-check passedBusiness, Finance & HR

Install Dossier

skills CLI
$ npx skills add borghei/Claude-Skills --skill dossier -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install borghei/Claude-Skills dossier --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/research/dossier .claude/skills/dossier && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
dossier
GitHub stars
881
Token cost
~2k tokens
SKILL.md length
815 words
Files
7 (incl. scripts, references)
Skills in repo
349
Repo updated
First seen
Licence
MIT

At a glance

Structured intelligence dossiers on companies, people, markets, or domains, with source triangulation and fact/inference discipline.

  • Works in 3 steps: Specify subject type + purpose. → Run dossier_outline_generator.py to… → Assign owners + research targets per…
  • Preparing a deal-prep dossier
  • SKILL.md covers When to use this skill, Inputs the advisor expects, Clarify First and Workflows, plus 6 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Dossier is an agent skill from borghei/Claude-Skills. Structured intelligence dossiers on companies, people, markets, or domains, with source triangulation and fact/inference discipline. Use when preparing a deal-prep dossier, executive briefing, or due-diligence overview.

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/dossier-frameworks-and-structure.md`, `references/fact-vs-inference-discipline.md` and `references/source-triangulation-and-reliability.md`).

It sits in Business, Finance & HR, covering Fundraising and pitch decks and Sales call preparation. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

When your agent uses it

  • Preparing a deal-prep dossier
  • Executive briefing
  • Due-diligence overview

Example prompts

  • “/dossier”

Requirements

  • Python 3

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Specify subject type + purpose.
  2. Run dossier_outline_generator.py to produce a structured outline
  3. Assign owners + research targets per section.

What it can do on your machine

Read from SKILL.md and the folder at commit 4a698e8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Dossier loads about 2k tokens when it runs, and up to ~6.8k if it reads all its reference files. Until then it costs about 57 tokens; SKILL.md has 815 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 815 words, ~1,957 tokens.

Download SKILL.mdSave it as .claude/skills/dossier/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
dossier
description
Structured intelligence dossiers on companies, people, markets, or domains, with source triangulation and fact/inference discipline. Use when preparing a deal-prep dossier, executive briefing, or due-diligence overview.
license
MIT + Commons Clause
metadata.version
1.0.0
metadata.author
borghei
metadata.category
research
metadata.domain
research
metadata.updated
2026-05-27
metadata.tags
dossier, intelligence, due-diligence, market-entry, briefing, research

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.
bash
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.
bash
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.
bash
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:

CategoryDefinitionExample
FactVerifiable, sourced"Founded 2018; HQ in Chicago"
InferenceReasoned from facts"Likely targeting enterprise segment based on hiring pattern"
SpeculationNo supporting evidence"Might pivot to AI next year"

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

Show full SKILL.md (389 more words)Show less
Source reliability scoring (Admiralty Code adapted)
ReliabilityCodeDescription
Completely reliableAEstablished, history of completely reliable info
Usually reliableBHistory of mostly reliable info
Fairly reliableCHistory of reliable info with notable errors
Not usually reliableDLimited history; mixed accuracy
UnreliableEKnown for inaccurate info
Cannot be judgedFNew / unknown source
Information credibilityCodeDescription
Confirmed1Confirmed by other independent sources
Probably true2Not confirmed; consistent with other info
Possibly true3Not confirmed; reasonable but unsupported
Doubtful4Inconsistent with other info
Improbable5Contradicted by other info
Cannot be judged6New 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"
  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
  • 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

© borghei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references) in research/dossier of borghei/Claude-Skills.

  • SKILL.md
  • references/dossier-frameworks-and-structure.md
  • references/fact-vs-inference-discipline.md
  • references/source-triangulation-and-reliability.md
  • scripts/dossier_outline_generator.py
  • scripts/fact_inference_separator.py
  • scripts/source_triangulation_validator.py

Open the folder on GitHubat commit 4a698e8

Compare with similar skills

Dossier next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Dossier compared with similar skills
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Dossier this skillborghei/Claude-Skills881—~2kAutomated safety check: PassMIT
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Company Researchmajiayu000/claude-skill-registry6661 repos~2.2kAutomated safety check: PassMIT
Apify Buying Signal Detectionapify/awesome-skills264—~5.1kAutomated safety check: NotesApache-2.0
Investor Outreachaffaan-m/ECC275k6 repos~664Automated safety check: PassMIT
Deep Contextkbanc85/claudia296—~1.4kAutomated safety check: PassCustom licence

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Questions about Dossier

What does Dossier do?

Structured intelligence dossiers on companies, people, markets, or domains, with source triangulation and fact/inference discipline. Dossier is an agent skill from borghei/Claude-Skills. Structured intelligence dossiers on companies, people, markets, or domains, with source triangulation and fact/inference discipline.

When should I use Dossier?

Dossier fits situations like: preparing a deal-prep dossier; executive briefing; due-diligence overview.

How do I install Dossier in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill dossier -a claude-code`. Or copy the skill folder (research/dossier in borghei/Claude-Skills) into .claude/skills/dossier in your project. Claude Code loads it when a task matches its description.

How do I install Dossier in Codex?

Run `npx skills add borghei/Claude-Skills --skill dossier -a codex`. Or copy the skill folder (research/dossier in borghei/Claude-Skills) into .agents/skills/dossier in your project. Codex loads it when a task matches its description.

Can I use Dossier in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add borghei/Claude-Skills --skill dossier -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dossier, .gemini/skills/dossier, .github/skills/dossier and .opencode/skills/dossier in your project.

What does Dossier need to run?

Going by SKILL.md and its folder, Dossier needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Dossier access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Dossier safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Dossier use?

Dossier is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Dossier use?

About 2k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.9k tokens, read only when the agent opens those files.

What are the alternatives to Dossier?

Skills that share tags, products or a category with Dossier: Investor Call Prep (gooseworks-ai/goose-skills, 1.2k stars), Company Research (majiayu000/claude-skill-registry, 666 stars), Apify Buying Signal Detection (apify/awesome-skills, 264 stars) and Investor Outreach (affaan-m/ECC, 275k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Dossier?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 881 GitHub stars. The repository holds 349 skills in this directory. The repository was last updated on October 7, 2026.

Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.