Org Report

Org Report

Generate a polished executive organization brief for a target person. The report includes:

• Cover page with target, generation timestamp, FTE / vendor counts, byline, methodology, and disclosure
• Full management chain (up to the top)
• Team index (color-coded)
• Individual profiles: chain, target, each team's FTEs, individual contributors
• Appendix: all contractors and vendors grouped by team

Output is a Word .docx, a .pdf rendered from it, and a live Copilot canvas view.

When to use

Trigger on any of:

• "Generate an org report for {Person}"
• "Build an org brief for {Person}"
• "Make an executive org report for {Person}"
• "Create an org profile document for {Person}"
• "Produce an organization brief for {Person}"

If the user asks for a report on themselves, use their profile as the target.

Prerequisites (verify before starting)

1. Directory MCP — a Model Context Protocol server that exposes org-tree queries and person profiles. This plugin was built against Microsoft's WorkIQ MCP (workiq-ask tool); any MCP that answers equivalent queries about a corporate directory and communication signals will work with minor prompt adjustments in Phases 2–4.
2. Python 3.11+ with python-docx and docx2pdf installed:

   pip install python-docx docx2pdf
   

3. Microsoft Word (Windows/macOS) — required by docx2pdf. On Linux, swap in LibreOffice via a headless converter and pass --pdf-out '' to skip in-script PDF.
4. Canvas extension — the org-directory extension should be installed at ~/.copilot/extensions/org-directory/. This plugin ships a copy in extensions/org-directory/; copy it once, then extensions_reload.
5. Configuration (optional) — cover byline, methodology, disclosure, base font, and vendor-detection rules can be customized via config.json. See § Configuration below. Without a config file the plugin uses tenant-neutral defaults.

If any prerequisite is missing, stop and tell the user what to install.

Workflow

Phase 1 — Confirm the target and reset state

Ask the user to confirm the target (UPN, email, or full name). Then create a fresh state file at ~/.copilot/extensions/org-directory/artifacts/directory.json:

{ "orgChart": null, "profiles": {}, "updatedAt": null }

Phase 2 — Resolve the org structure via the directory MCP

Use the MCP's directory query (e.g., WorkIQ workiq-ask, or workiq-fetch on /users/... where available) to build the tree:

1. Target profile: get displayName, jobTitle, department, email, officeLocation.
2. Management chain: walk up via /users/{id}/manager until you reach the top (e.g., the CEO). Save as managementChain (ordered top → target's manager).
3. Direct reports: recursively fetch /users/{id}/directReports for the target and every descendant. Attach as nested reports: [...].

Persist to directory.json:

{
  "orgChart": {
    "managementChain": [ { "displayName": "...", "jobTitle": "..." }, ... ],
    "target": { "displayName": "...", "jobTitle": "...", "email": "...", "department": "..." },
    "directReports": [
      { "displayName": "...", "jobTitle": "...", "email": "...",
        "reports": [ { "displayName": "...", ... } ] }
    ]
  },
  "profiles": {},
  "updatedAt": "2026-01-01T00:00:00Z"
}

Vendor detection: in tenants that use the First Last (Company Name) display-name convention (Microsoft is one example), contractors are identified by that parenthetical plus an email prefix. Both signals are configurable — see vendor_detection in scripts/config.example.json. Without configured rules the plugin treats all directory entries as FTEs.

Phase 3 — Enrich every person's profile

For every person in the tree (target + all descendants), call the directory MCP in parallel batches of 10–15 with this exact prompt:

For {Full Name} ({title, if known}, in {target}'s org), produce a concise
professional profile grounded in accessible communication signals (email,
meetings, chat, documents). Return ONLY this JSON in a ```json fence:

{
  "displayName": "{Full Name}",
  "jobTitle": "...",
  "department": "...",
  "email": "...",
  "summary": "2-3 sentence executive summary of their role and focus areas",
  "recentWork": ["3-6 recent projects or themes"],
  "topics": ["4-8 short tags describing what they work on"],
  "expertise": ["3-6 specific skills or domains"],
  "collaborators": ["6-8 people they work most closely with"],
  "signalDensity": "high | medium | low | none",
  "signalCounts": { "emails": 0, "meetings": 0, "chats": 0, "docs": 0 },
  "signalCountsWindow": "e.g. Jul-Aug 2026",
  "officeLocation": "..."
}

About the new optional fields:

• signalDensity — coarse indicator of how much verifiable signal grounded this profile. Use high when 30+ signals, medium for 10-30, low for 3-10, none for < 3. Renderer displays a colored dot next to the name.
• signalCounts — approximate counts per channel over the last 60 days. The renderer prints "Grounded in N emails · N meetings · N chats · N docs ({signalCountsWindow})" as an attribution footer. Skip channels with 0.
• signalCountsWindow — the human-readable date range the counts cover.

Rules:

• Parallel batches only. MCP directory calls can take 10–60 s per query. Fire 10–15 calls in a single response, never sequential loops.
• Retry MCP failures individually. No MCP client found and timeouts happen — retry the specific failed call once.
• Self-identify. The displayName field lets you match responses back to people even in a mixed batch.
• Merge into state. Key by displayName.lower().strip(). Update updatedAt on each profile.
• Empty responses. If the MCP returns nothing usable (common for niche contractors), store:

  "collaboratorsNote": "Collaborator network not surfaced in accessible signals"
  

• Skip execs above the target. External executives (CEO, presidents, large-org GMs) have collaborators legitimately outside the org and produce noisy profiles. Enrich the target and everyone below; leave upstream chain members as chain entries only.

Phase 4 — (Optional) Validate collaborators

The first-pass collaborator list often includes people from unrelated meetings. For any profile whose collaborators look off (mostly outside the org, unfamiliar names), do a second pass with a narrower prompt:

Who are the 6-8 people {Name} ({title/company}, in {target}'s org) works most
closely with day-to-day? Return only this exact JSON in a ```json fence:
{"person": "{Name}", "collaborators": ["Name1", "Name2", ...]}

Same batch pattern (10–15 parallel). Merge overwrites the previous collaborators list and clears any collaboratorsNote. Accept ~5% empties.

Phase 4.2 — (Optional) Deep dive for the target and direct reports

For the target and each of their direct reports, run a second MCP pass with a longer prompt to fill the deepDive object. This costs an extra ~10-25 MCP calls per report but adds a dedicated "DEEP DIVE" section to the highest-signal profiles.

For {Full Name} ({title}, in {target}'s org), summarize the leadership shape
of their work in the last 6 months, grounded strictly in accessible
communication signals. Return ONLY this JSON in a ```json fence:

{
  "displayName": "{Full Name}",
  "deepDive": {
    "strategicBets": ["3-5 concrete initiatives or bets they are driving"],
    "recentDecisions": ["3-5 explicit decisions or trade-offs they have made"],
    "crossTeamDependencies": ["3-5 dependencies on other teams or partners"]
  }
}

Same parallel-batch rules as Phase 3. Merge by displayName.lower().strip() — deepDive overwrites any prior deepDive object. Skip anyone not in target + directReports — depth beyond that is noisy and expensive.

Phase 4.5 — (Optional) Fetch profile photos

If your application layer supplies a photo fetcher (e.g., the Microsoft Graph fetcher at OrgReports/scripts/fetch_photos.py), run it now to populate the photo cache. The renderer picks photos up automatically if they land at <photos.directory>/<email>.jpg (see § Configuration).

python scripts/fetch_photos.py

Photos are optional — skip this phase and the report renders name-only cards.

Phase 5 — Generate the DOCX + PDF

Run the export script. It reads directory.json, writes the DOCX and PDF, and copies them into the canvas extension's artifacts folder. If a config.json lives in the current working directory, cover copy and vendor rules load from it; otherwise built-in tenant-neutral defaults apply.

python ~/.copilot/installed-plugins/alex-mall/org-report/scripts/export_org.py

# Explicit config path:
python ~/.copilot/installed-plugins/alex-mall/org-report/scripts/export_org.py --config config.json

If that path does not resolve, the plugin was installed by a route other than the Alex ACT Mall. Locate the installed scripts/export_org.py under ~/.copilot/installed-plugins/ and use that path instead of guessing.

Optional flags:

• --state <path> — override the state file (default: canvas artifacts)
• --docx-out <path> — override the DOCX output path
• --pdf-out <path> — override the PDF output path (set to empty string to skip PDF)
• --config <path> — explicit config file path (default: ./config.json, then user scope, then built-in defaults)

Phase 6 — Refresh the canvas

extensions_reload
open_canvas({ canvasId: "org-directory", instanceId: "org-report-1" })

The canvas embeds the fresh PDF with a "Download PDF" button.

Phase 7 — Report completion

Tell the user:

• Target name and how many FTE + vendor profiles were enriched
• Where the DOCX lives (path)
• That the canvas is open and refreshable

Editing the cover copy

Cover byline, methodology paragraph, and disclosure paragraph are all configurable via config.json. See § Configuration below. The default disclosure covers three things every exec brief of this kind should say:

1. Data-access limits — information barriers, sensitivity labels, DLP policies
2. AI accuracy — summaries may contain errors, verify before acting
3. Confidentiality — organizational confidential personnel info, do not redistribute

Configuration

export_org.py loads its cover copy, byline, base font, prose labels, vendor rules, and photo settings from config.json. Discovery order:

1. --config PATH (explicit CLI flag)
2. ./config.json in the current working directory
3. ~/.copilot/extensions/org-directory/config.json (user-level default)
4. Built-in tenant-neutral defaults

Any subset of keys is valid; missing keys fall back to defaults. See scripts/config.example.json for the full schema and a starting template.

Available config sections

Profile photos

Set photos.directory to a folder of image files named <email>.jpg (or .jpeg / .png). The renderer looks up each entry's email (with .upn fallback), then their normalized displayName. Missing photos are silently skipped. The plugin does not fetch photos itself — pair it with an application-layer fetcher (see OrgReports' scripts/fetch_photos.py for the Microsoft Graph reference implementation).

For the Microsoft-tenant configuration used by the OrgReports application, see that repo's config.json.

Known limits

• MCP latency: directory queries can take 10–60 s each; some questions run minutes. Always batch in parallel.
• MCP flakiness: occasional No MCP client found / timeouts. Retry the specific failed call once.
• Empty profiles: ~5–10% of contractors have no surfaceable signals. Mark with collaboratorsNote and move on.
• Vendor name format: relies on the First Last (Company) directory convention. Configure vendor_detection.email_prefixes and display_name_paren_excludes in config.json for your tenant.
• Directory vs contacts: /users/{id} is the corporate directory; /me/contacts is personal contacts. IDs are not interchangeable.
• Binary content: most directory MCPs don't yet expose files or profile photos as bytes — only structured metadata.
• docx2pdf on Windows: requires Microsoft Word. On macOS/Linux, substitute LibreOffice or a headless converter and pass --pdf-out ''.