Docsagent
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Search and manage private, local document collections (PDF, PPTX, DOCX) offline.
Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile.
Install Dossier
$ npx skills add alirezarezvani/claude-skills --skill dossier -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install alirezarezvani/claude-skills dossier --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/research/dossier/skills/dossier .claude/skills/dossier && rm -rf skills-srcUse ~/.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/
Install the "dossier" agent skill from https://github.com/alirezarezvani/claude-skills/tree/main/research/dossier/skills/dossier into .claude/skills/dossier/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dossier", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/alirezarezvani/claude-skills/tree/main/research/dossier/skills/dossierType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add alirezarezvani/claude-skills --skill dossier -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install alirezarezvani/claude-skills dossier --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/research/dossier/skills/dossier .agents/skills/dossier && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "dossier" agent skill from https://github.com/alirezarezvani/claude-skills/tree/main/research/dossier/skills/dossier into .agents/skills/dossier/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dossier", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add alirezarezvani/claude-skills --skill dossier -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install alirezarezvani/claude-skills dossier --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/research/dossier/skills/dossier .cursor/skills/dossier && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "dossier" agent skill from https://github.com/alirezarezvani/claude-skills/tree/main/research/dossier/skills/dossier into .cursor/skills/dossier/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dossier", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/alirezarezvani/claude-skills.git --path research/dossier/skills/dossier--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add alirezarezvani/claude-skills --skill dossier -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install alirezarezvani/claude-skills dossier --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/research/dossier/skills/dossier .gemini/skills/dossier && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "dossier" agent skill from https://github.com/alirezarezvani/claude-skills/tree/main/research/dossier/skills/dossier into .gemini/skills/dossier/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dossier", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install alirezarezvani/claude-skills dossierInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add alirezarezvani/claude-skills --skill dossier -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/research/dossier/skills/dossier .github/skills/dossier && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "dossier" agent skill from https://github.com/alirezarezvani/claude-skills/tree/main/research/dossier/skills/dossier into .github/skills/dossier/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dossier", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add alirezarezvani/claude-skills --skill dossier -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install alirezarezvani/claude-skills dossier --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/research/dossier/skills/dossier .opencode/skills/dossier && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "dossier" agent skill from https://github.com/alirezarezvani/claude-skills/tree/main/research/dossier/skills/dossier into .opencode/skills/dossier/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dossier", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
dossier- GitHub stars
- 28k
- Token cost
- ~4.2k tokens
- SKILL.md length
- 1,920 words
- Files
- 7 (incl. scripts, references)
- Skills in repo
- 342
- Repo updated
- First seen
- Licence
- MIT
At a glance
Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile.
- Works in 10 steps: Grill-Me Intake (6 forcing questions,… → Subject Disambiguation → Source Matrix Selection → …
- The user asks for background research
- SKILL.md covers Non-Generic Framing — The…, Agent Integrity Rules…, Phase 1: Grill-Me Intake (6… and Phase 2: Subject Disambiguation, plus 11 more sections
- Runs Python scripts from its folder; calls python3
What it does
Dossier is an agent skill from alirezarezvani/claude-skills. Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile. Forcing intake makes the user state their hypothesis upfront (what they already believe and want to verify or disprove) so the dossier tests it rather than confirms it. Output is an editable Word document (.docx) with verdict on the hypothesis, identity facts, 12-month activity timeline, network and reputation signals, red flags, conversation hooks tied to…
Its SKILL.md is about 4.2k 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/conversation_hook_quality.md`, `references/hypothesis_testing_discipline.md` and `references/subject_type_source_matrix.md`).
It sits in Documents & Office, covering Word documents, MCP servers and Sales call preparation. It works with Microsoft Word, GitHub and SEC EDGAR. The repository describes itself as: 380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8… The licence is MIT.
When your agent uses it
- The user asks for background research
- Meeting prep on a specific entity (e.g.
- Prep me for a meeting with [person/company]
- Due diligence on [company])
Example prompts
- “prep me for a meeting with [person/company]”
- “due diligence on [company]”
- “/dossier”
Requirements
- Python 3
- Node.js
Workflow steps
10 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 19392f7. 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 4.2k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 239 tokens; SKILL.md has 1,920 words of instructions outside code blocks.
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 alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 1,920 words, ~4,187 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
- Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile. Forcing intake makes the user state their hypothesis upfront (what they already believe and want to verify or disprove) so the dossier tests it rather than confirms it. Output is an editable Word document (.docx) with verdict on the hypothesis, identity facts, 12-month activity timeline, network and reputation signals, red flags, conversation hooks tied to specific findings, and source-provenance audit log. Uses WebSearch + WebFetch + free APIs (SEC EDGAR, GitHub, ProPublica) as workhorses; optional BYOK MCPs enhance coverage. Use when the user asks for background research, diligence, or meeting prep on a specific entity (e.g., 'prep me for a meeting with [person/company]', 'due diligence on [company]'). Honors sensitivity exclusions for journalism + personal-vetting contexts.
- license
- MIT
- metadata.source_spec
- megaprompts/12-dossier-megaprompt.md
- metadata.build_pattern
- Path B (direct conversion)
- metadata.research_pack_convention
- Agent Integrity Rules verbatim per PR #657 audit; hypothesis-testing variant
- metadata.version
- 1.0.0
Dossier — Decision-Grade Entity Research
Portability: Requires
WebSearch+WebFetch, Node.js withdocxpackage, and optionallybash_tool+curlfor free APIs (SEC EDGAR, GitHub, ProPublica). BYOK MCPs (LinkedIn, Crunchbase, Apollo, Pitchbook, SimilarWeb) are optional enhancements. Works in Claude Code CLI natively.
Non-Generic Framing — The Differentiator
This skill is decision-grade entity research with hypothesis-testing. It refuses to be "tell me about Microsoft". Every invocation forces the user to expose their hypothesis upfront (Q4) so the dossier tests it rather than confirms it.
The use case shape:
"I'm pitching Microsoft Tuesday. My hypothesis is they're consolidating AI spend on their first-party Foundry platform. Validate or disprove, and give me three conversation hooks tied to what you find."
NOT:
"Tell me about Microsoft."
The forcing Q4 — the hypothesis question — is the non-generic anchor. Skip it and the skill produces a Wikipedia summary.
See references/hypothesis_testing_discipline.md for the canon.
Agent Integrity Rules (Research-Pack Convention)
Locked verbatim per PR #657 audit.
- Execution discipline. Sequential search calls. WebSearch + WebFetch have looser rate limits than Consensus but still apply 1 q/sec etiquette. Confirm response received before next call.
- Source discipline. Cite only sources returned by this session's tool calls. Wikipedia / training knowledge labeled
[Background — verify before quoting]and excluded from primary findings count. - Three-count tracking. Queries sent / sources received / sources cited. Plus per-tier breakdown (primary / secondary / tertiary) unique to dossier. Surfaced in audit log.
- Retry policy. On failure → wait 3s → retry once → log. After 3 consecutive failures: stop, alert user.
- Source reliability tier. Each citation tagged primary (official, SEC, court records) / secondary (mainstream news, trade press) / tertiary (blogs, forums). DOCX surfaces tier on every flag.
Phase 1: Grill-Me Intake (6 forcing questions, one at a time)
Q1 (root) — Subject identity
Who is the subject? Give me the exact name and, if a company, the website or LinkedIn URL. If a person, their LinkedIn URL or a unique identifier (company affiliation + role).
Why I'm asking: Disambiguation. There are 47 John Smiths. There are three companies called "Atlas". I need a specific entity to research.
If user gives only a name, push for a second identifier. Refuse to proceed on ambiguous names.
Q2 (depends on Q1) — Subject type
What kind of subject is this? Pick one: person / company / nonprofit / government org / other.
Why I'm asking: Different source matrices apply. For people I check LinkedIn, GitHub, Scholar, news; for companies I check SEC EDGAR (if public), Crunchbase, news, GitHub for tech orgs; for nonprofits I check Form 990s on ProPublica.
Forcing choice. "Other" requires a one-line description.
Q3 (depends on Q2) — Purpose
What are you preparing for? Pick one:
- Sales meeting / partnership pitch
- Investment diligence
- Acquisition diligence
- Journalism / due diligence
- Job interview prep
- Competitive intelligence
- Personal vetting (date, hire, business partner)
- Other (specify)
Why I'm asking: The purpose dictates the angle, the depth, and the red-flag sensitivity. Sales prep needs conversation hooks. Investment diligence needs traction signals. Personal vetting needs careful sensitivity boundaries.
Q4 (depends on Q3) — Hypothesis — MANDATORY
What's your hypothesis going in? What do you already believe about this subject, and what do you want to verify or disprove?
Why I'm asking: This is the critical question. A dossier that just confirms what you already think is worthless. By stating your hypothesis upfront, I can search for evidence that would disprove it as well as evidence that supports it — and give you a verdict you can actually use.
Examples:
- "I believe Microsoft is consolidating AI spend on first-party Foundry. Verify or disprove."
- "I think the CEO is over their head — too much TAM talk, no traction. Test that."
- "I believe this nonprofit's overhead ratio is sketchy. Check the 990s."
- "I think this person is technical enough to handle a CTO role. Verify."
MANDATORY. If user says "I don't have one", push back once: "Then guess. Commit to a position you can update later. The dossier needs a hypothesis to test, otherwise it's a generic profile and won't help you make a decision."
If still refused: fall back to implicit hypothesis "what's the most surprising thing I could find?" and flag the fallback in audit log.
This question is the non-generic anchor. Skip it and the skill becomes a Wikipedia summary.
Q5 (depends on Q3) — Depth
Time horizon: 5-minute brief or 15-minute decision-grade dossier?
Why I'm asking: Brief mode caps at ~10 searches and skips the network + reputation passes. Decision-grade goes deeper on every section. Pick based on how much skin you have in this decision.
Forcing choice.
Q6 (asked only if Q3 ∈ {journalism, personal vetting}) — Sensitivities
Anything sensitive to exclude? E.g., personal medical, family details, political history, or specific topics off-limits?
Why I'm asking: Some research contexts have ethical constraints. I'd rather know upfront than surface something you'd never share.
Skip for sales/investment/acquisition/competitive intel (low sensitivity); ask for journalism/personal vetting (high sensitivity).
Stop condition: After Q6 (or earlier with dependency skips), commit and start Phase 2. Never re-open intake after Phase 2 begins.
Phase 2: Subject Disambiguation
Before Phase 3, resolve the subject to a specific entity:
- For people: confirm LinkedIn URL OR (employer + role + city)
- For companies: confirm domain OR (legal name + incorporation jurisdiction)
- For nonprofits: confirm EIN OR (legal name + state)
- For government orgs: confirm official .gov URL
If still ambiguous after Q1 push-back: halt and re-ask Q1 with disambiguating identifiers. Refuse to proceed.
Phase 3: Source Matrix Selection
Routed by Q2 subject type. See references/subject_type_source_matrix.md for the full canon.
Person
- LinkedIn (manual fetch or LinkedIn MCP if BYOK)
- Personal website
- Twitter/X (rate-limited; degrade gracefully)
- GitHub (if technical subject)
- Google Scholar (if academic)
- News (WebSearch + WebFetch)
- Conference talk transcripts, podcasts (WebSearch)
Company
- Official website (about, leadership, news, careers)
- SEC EDGAR (free API; 10-Ks, 10-Qs, 8-Ks for public co's)
- Crunchbase free tier (or Crunchbase MCP if BYOK)
- News (WebSearch + WebFetch)
- GitHub (for tech orgs)
- Glassdoor + Comparably (sentiment; degrade gracefully if scraping blocked)
- LinkedIn company page
Nonprofit
- ProPublica Nonprofit Explorer (free; Form 990s)
- Official website
- News
- GuideStar (if accessible)
Government org
- Official .gov sites
- News
- ProPublica (for federal agencies)
If a paid MCP is connected (Apollo, Pitchbook, SimilarWeb), use it but mark findings as BYOK-sourced in the audit log.
Phase 4: Hypothesis-Driven Search
Every Phase 4 search MUST be classified as either:
- Supporting evidence (confirms hypothesis), OR
- Disconfirming evidence (would refute hypothesis)
≥30% of search budget allocated to disconfirming queries. Enforced via scripts/disconfirming_evidence_balance.py.
Example for hypothesis "Microsoft is consolidating AI spend on Foundry":
- Supporting: "Microsoft Foundry adoption 2026", "Microsoft AI infrastructure consolidation"
- Disconfirming: "Microsoft OpenAI deal renegotiation", "Microsoft AI vendor diversification", "Microsoft third-party model partnerships 2026"
This is what makes the dossier decision-grade rather than confirmation-biased.
For each search:
- Record via
citation_tracker.pywith classification (supporting / disconfirming) - Apply source tier from
source_tier_classifier.pyto each result URL
Phase 5: 12-Month Activity Timeline
Default 12-month window for activity timeline; deeper for foundational identity.
Categories:
- News (acquisitions, hires, departures, product launches)
- Funding rounds / financial events
- Controversies / legal events
- Public statements / strategy shifts
Reverse chronological. Each entry hyperlinked + tiered.
Show full SKILL.md (769 more words)Show less
Phase 6: Network + Reputation Signals
Network
- Companies: investors (in/out), customers (named), partners
- People: co-founders, advisors, mentors, employers, board roles
- Nonprofits: funders, board, leadership
5-10 entries, ranked by relevance to hypothesis.
Reputation
- Sentiment from news (recent 12 months)
- Glassdoor for companies (overall rating + 3 representative reviews)
- Peer mentions for people
- Caveat: reputation data is noisy; tier accordingly
Phase 7: Red-Flag Pass
Surface but don't sensationalize:
- Litigation (court records → primary tier)
- Regulatory actions (SEC, DOJ, agency actions → primary)
- Unusual departures (key personnel exits within 90 days)
- Financial signals (going-concern notes in 10-Ks → primary)
- Reputation hits (sustained negative coverage → secondary)
Each flag tiered. Tier shows up next to every flag in the DOCX.
Phase 8: Conversation Hook Generation
3-5 specific hooks tied to actual findings, not generic talking points.
See references/conversation_hook_quality.md for the canon.
| ❌ Generic | ✅ Finding-tied |
|---|---|
| "Ask about their roadmap" | "Mention their recent acquisition of [X] — it signals they're investing in vertical Y. Suggested framing: 'Saw the [X] announcement — how does that change your roadmap on Y?'" |
| "Ask about hiring" | "Their VP Engineering left 3 weeks ago (LinkedIn). Suggested framing: 'I noticed [name] moved on — what's the eng leadership plan?'" |
| "Talk about their values" | "They updated their pricing page last week (their official site). Suggested framing: 'Saw the pricing refresh — what drove that?'" |
Each hook:
- The hook (one sentence)
- The finding it's tied to (with hyperlink + tier)
- Suggested framing (verbatim phrasing user can adapt)
Phase 9: DOCX Generation (9 Sections)
Via Node.js + docx library.
- Executive Summary — one paragraph: who they are + why they matter + verdict on the hypothesis (SUPPORTED / PARTIALLY SUPPORTED / DISPROVEN / INCONCLUSIVE) + 3 things-you-should-know bullets.
- Identity Facts Table — founded/born, location, size/stage, current role, key affiliations. All cells sourced; hover-text tier.
- Hypothesis Test — user's hypothesis stated verbatim. Supporting evidence (3-5 bullets with hyperlinked citations). Disconfirming evidence (3-5 bullets with hyperlinked citations). Verdict paragraph (2-3 sentences explaining the weight).
- 12-Month Activity Timeline — News, funding, hires, departures, product launches, controversies. Reverse chronological. Each entry hyperlinked.
- Network Signals — Collaborators / investors / associates. 5-10 entries, ranked by relevance to hypothesis.
- Reputation Signals — Sentiment from news, Glassdoor for companies, peer mentions for people. Caveat: reputation data is noisy.
- Red Flags + Hidden Patterns — Litigation, regulatory actions, unusual departures, financial signals, reputation hits. Tiered.
- Conversation Hooks — 3-5 specific hooks tied to findings. Each: hook + finding + suggested framing.
- Source Provenance + Audit Log — Per-source list with tier. Search summary table (#, query, classification, sources returned, sources cited). Three counts + per-tier counts. Failed searches. BYOK-MCP usage flag.
Styling
Arial 12pt body, navy headings (#1a3a5c), light blue table headers (#e8f0f8), red red-flag callout, green conversation-hook callout.
Hyperlink patterns
new ExternalHyperlink({
link: "https://...",
children: [new TextRun({ text: title, style: "Hyperlink" })],
});Phase 10: Deliver
- Save:
<output-dir>/dossier_<entity-slug>_<YYYY-MM-DD>.docx - Chat summary: file path + verdict on hypothesis + audit counts + tier breakdown + BYOK MCPs used (if any)
- Validate: check zip integrity with
python3 -c "import zipfile,sys; zipfile.ZipFile(sys.argv[1]).testzip()" <docx>(no output = intact), then confirm the required sections are present
Tooling
| Script | Role |
|---|---|
scripts/citation_tracker.py | Three-count audit + supporting/disconfirming classification + source-tier tagging at ~/.dossier_sessions/<session>.json |
scripts/disconfirming_evidence_balance.py | Verifies ≥30% of search budget allocated to disconfirming queries; warns if biased |
scripts/source_tier_classifier.py | URL → primary / secondary / tertiary classification via domain heuristics |
References
references/hypothesis_testing_discipline.md— ≥30% rule + decision-grade vs encyclopedic (7+ sources)references/subject_type_source_matrix.md— person/company/nonprofit/gov source matrices (7+ sources)references/conversation_hook_quality.md— finding-tied hook discipline (7+ sources)
Error Handling
| Failure | Behavior |
|---|---|
| Subject name ambiguous | Refuse to proceed. Re-ask Q1 with disambiguating identifier. |
| User refuses to state hypothesis | Push back once. If still refused, fall back to "what's the most surprising thing I could find?" implicit hypothesis. Flag in audit. |
| Subject has zero public footprint | Surface explicitly. Suggest different name or early-stage. Don't fabricate. |
| LinkedIn scrape blocked | Note in audit; fall back to WebSearch; suggest user verify manually. |
| SEC EDGAR fails | Retry once. If still failing, note "public filings not retrieved" and continue. |
| Sentiment data sparse | Mark reputation section as "limited public signal"; don't infer from training. |
| Sensitive topic surfaces (Q6 exclusion) | Exclude from DOCX. Note in chat (not in DOCX) so user knows the exclusion was honored. |
| 3 consecutive tool failures | Stop, alert user, share collected so far. |
| DOCX generation fails | Save raw data as JSON fallback. |
Anti-Patterns To Reject
- Producing a dossier without forcing Q4 hypothesis
- Allocating <30% of search budget to disconfirming evidence
- Batching intake questions
- Accepting ambiguous subject names
- Generic conversation hooks ("ask about their roadmap")
- Sensationalizing red flags (tier them, don't editorialize)
- Skipping the source-reliability tier on flags
- Fabricating coverage when LinkedIn or scraping is blocked
- Using BYOK-MCP data without flagging in audit log
- Including sensitive topics user excluded in Q6
- Confirmation-biased verdict ("SUPPORTED" without engaging with disconfirming evidence)
Version: 1.0.0
Source spec: megaprompts/12-dossier-megaprompt.md (maintainer-local draft spec — gitignored, not present in the public repository)
Build pattern: Path B (direct conversion). Research-pack sibling, hypothesis-testing variant.
© alirezarezvani, 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/skills/dossier of alirezarezvani/claude-skills.
- SKILL.md
- references/conversation_hook_quality.md
- references/hypothesis_testing_discipline.md
- references/subject_type_source_matrix.md
- scripts/citation_tracker.py
- scripts/disconfirming_evidence_balance.py
- scripts/source_tier_classifier.py
Open the folder on GitHubat commit 19392f7
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Dossier this skillalirezarezvani/claude-skills | 28k | — | ~4.2k | Automated safety check: Pass | MIT | |
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| Officeclimateaix/mateclaw | 1.1k | — | ~844 | Automated safety check: Pass | Apache-2.0 | |
| Government WritingPinvou/pinvou-agent | 2.4k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Learniurykrieger/claude-bedrock | 105 | — | ~6.5k | Automated safety check: Notes | MIT |
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Questions about Dossier
What does Dossier do?
Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile. Dossier is an agent skill from alirezarezvani/claude-skills. Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile.
When should I use Dossier?
Dossier fits situations like: the user asks for background research; meeting prep on a specific entity (e.g; prep me for a meeting with [person/company]; due diligence on [company]).
How do I install Dossier in Claude Code?
Run `npx skills add alirezarezvani/claude-skills --skill dossier -a claude-code`. Or copy the skill folder (research/dossier/skills/dossier in alirezarezvani/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 alirezarezvani/claude-skills --skill dossier -a codex`. Or copy the skill folder (research/dossier/skills/dossier in alirezarezvani/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 alirezarezvani/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; Node.js.
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 4.2k tokens (SKILL.md is roughly 17k 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 6.4k 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: Docsagent (docsagent/docsagent, 625 stars), Markit (shift-labs-ai/markit, 1.3k stars), Officecli (mateaix/mateclaw, 1.1k stars) and Government Writing (Pinvou/pinvou-agent, 2.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Dossier?
alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,829 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.
Source: alirezarezvani/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.