Wiki Knowledge That Stays Found
Search wikis across title, description, and full body content with tag filters and admin-only status visibility. Inspect version history with author attribution, dates, and change types. Three admin writes — create draft, change status, soft-delete — all sit in RISKY_TOOLS behind explicit confirmation.
Why Wikis Become Write-Only Archives
Wikis Agent attacks the four specific failures that turn an active wiki into an unread archive — without forcing teams to re-author what they've already written.
Title-Only Search Misses The Content Inside The Wiki
A wiki titled "Engineering Onboarding Guide" contains the exact answer to a security question in section 4. Search-by-title doesn't surface it. Full-body search is the difference between a wiki that gets read and a wiki that gets re-written.
Version History Is Invisible Without Opening Every Wiki
"When did the on-call escalation matrix last change?" requires opening the wiki, finding the version control panel, scrolling. The agent surfaces version history with author, date, and change type in one prompt — no manual archaeology.
Threaded Discussion Lives Separately From The Wiki Itself
Wiki comments capture institutional context — "we tried this in 2024 and it failed because…" — that never makes it into the body. Without a way to surface threaded comments alongside the wiki, that context disappears with the conversation.
Admins Don't See What's Old, Stale, Or Unread
"Which wikis are nobody reading?" "Which were last updated 18 months ago?" Without get_wiki_stats rolling that up automatically, the wiki garden becomes a wiki jungle within two product cycles.
Conflicting Wikis Coexist Because Nobody Notices The Duplicates
"PTO Policy" exists in the HR space. "Time Off Guidelines" exists in the People Ops space. They contradict each other on the carryover rule. Employees follow whichever they find first. Without surfacing near-duplicate titles or overlapping content, the wiki becomes a maze of subtly wrong answers.
Draft Wikis Get Started And Then Abandoned For Months
A subject expert opens a draft, writes three paragraphs, gets pulled into something else, and never comes back. The draft sits in the system for a year. Without a "stale drafts by author" view, the wiki team keeps starting fresh instead of nudging the existing drafts across the finish line.
Wikis Agent At A Glance
Wikis AI
Full-body search · version + comments · gated admin writes.
Inside Wikis Agent — The Actual Capabilities
Every block below maps to a real tool the agent uses against your Wikis data. Seven read tools cover search, content, metadata, listing, version history, comments, and statistics. Three write tools — create_wiki, update_wiki_status, delete_wiki — are gated by admin role plus explicit confirmation.
Full-Body Search With Tag Filters And Admin Status Scope
Employees ask in plain English; the agent searches title, description, and full body content. Tag filters narrow the scope; admins can additionally filter by status (draft / published / archived). Once a result is selected, the agent returns the full body and rich metadata in structured form.
- search_wikis — natural-language search across title + description + body, with optional tag and (admin-only) status filters.
- get_wiki_content — full body content of a specific wiki by id or title match.
- {"get_wiki_details — metadata" => "author, dates, version count, view count, tags, permissions, status."}
- list_wikis — published wikis sorted by recent / popular / title, optionally tag-filtered.
Version History And Threaded Comments — Audit-Grade
"When did this wiki last change, and who reviewed it?" gets a structured answer — version numbers, change types, authors, and dates in chronological order. Threaded comments surface institutional context that lives outside the wiki body. Both are read-only and pull from the wiki's actual audit log, not the model's recollection.
- get_wiki_versions — version history with version number, change type, author, date, defaulting to 10 versions.
- get_wiki_comments — threaded comments including replies, defaulting to 20 top-level comments.
- get_wiki_stats — total count, status breakdown, most-viewed wikis, recently-updated wikis (admin dashboard).
- Read-only on history — the agent surfaces the audit trail but never rewrites it.
Three Admin Writes — Create, Status, Delete — All Gated
create_wiki writes a draft (title, optional body, optional tags) — never auto- publishes. update_wiki_status flips between draft / published / archived behind explicit confirmation. delete_wiki is a soft-delete (restorable by admin), and the confirmation prompt surfaces that. Non-admins cannot invoke any of these.
- create_wiki — creates a DRAFT wiki with title + optional body + optional tags. Drafts never auto-publish.
- update_wiki_status — moves between draft, published, archived. Each transition is confirmation-gated.
- delete_wiki — soft-delete; restorable by admin. The confirmation prompt explicitly surfaces "restorable" so the admin knows the action is reversible.
- Admin role required — the permission check happens before the LLM ever sees the tool as available; non-admins cannot invoke writes.
Outcomes Teams Can Measure
The agent's job is to make wiki bodies findable, surface change history without manual navigation, and keep admin writes safely gated. Measure against your pre-agent baseline.
- Body-search hit rate — share of wiki queries that returned a relevant result via body content vs title-only match.
- Wiki re-author rate — drop in new wikis created on topics that already had wiki coverage; if the agent surfaces existing wikis well, duplicates fall.
- Version-history adoption — share of "when did X change?" questions answered through get_wiki_versions vs manual page navigation.
- Stale-wiki burndown — wikis last-updated >12 months ago either refreshed or archived per quarter.
- Admin-write override rate — share of confirmation prompts cancelled vs confirmed; high cancellation indicates the agent is being too aggressive on proposals.
Three Admin Writes, Always With A Human In The Loop
Wikis Agent's RISKY_TOOLS list is 3 entries — create_wiki, update_wiki_status, delete_wiki. Every one requires admin role AND explicit confirmation. Employees use the agent in read-only mode; admins get write authority with every action surfaced for approval.
- 3 RISKY admin writes — create_wiki, update_wiki_status, delete_wiki. All admin-only + confirmation-required.
- create_wiki produces drafts — never published silently; status transitions are a separate explicit call.
- delete is soft — restorable by admin, and the confirmation prompt makes that visible.
- Status filter is admin-only — non-admins searching wikis can only see published; admins can scope search to draft or archived.
WHAT TEAMS TRY INSTEAD
The four alternatives — and none of them search your full wiki body, honor your draft/archive states, or gate admin writes
Wiki knowledge usually decays the day after launch. Search returns titles only, drafts leak into published results, and "is this still current" requires a manual sweep. None of the alternatives keep version history, threaded comments, and admin status visibility in one auditable model.
ChatGPT, Claude, or Copilot ("write a wiki about our deploy process")
Generic AI guessing from no source
- Wikis Agent searches the actual wiki body — not just titles, not the open web
- Version history with author attribution surfaces what changed and when — generic AI has no history
- create_wiki produces a draft an admin reviews and publishes; generic AI's output is just text
Confluence AI, Notion AI, Guru AI
Vendor wiki AI — separate seat, separate audit, draft/published bleed
- Reads wiki bodies alongside the rest of the platform (HRIS, training, policies) — vendor AI sees only its wiki silo
- Status filter is admin-only — non-admins never see drafts; vendor tools too often leak unpublished content
- One audit trail; vendor wiki AI forces parallel SSO and ACL sync that drifts the day someone changes team
Glean / generic enterprise search bolted on top
A search vendor crawling the wiki — no write back, no governance
- Knows the wiki app's draft/archive/published states natively — Glean indexes whatever it crawled, regardless of status
- Threaded comments and version history are part of the result, not a separate tool to open
- Three admin write actions in the same agent — Glean is read-only and never closes the "create / update / archive" loop
"We're not allowed to use AI on internal wikis"
The status quo — search returns 200 results, nobody reads them
- Full-body semantic search means the right page surfaces from a question, not a keyword guess
- Soft-delete with admin-only confirmation — wikis stay restorable when "delete this" turns out to be wrong
- Status transitions (draft → published → archived) flow through the agent with explicit admin confirmation
PLATFORM ADVANTAGE
Wikis Agent inherits everything the platform already runs
A standalone wiki tool has to plumb each of these. Wikis Agent gets them for free.
Full-body search, not just titles
Search hits the wiki body, description, and tags — not just titles. Knowledge buried in a long page still surfaces.
Status-aware visibility
Non-admins see only published wikis. Admin search can scope to draft or archived — clean separation, no accidental leaks.
Version history with author attribution
Inspect who changed what and when — the version log is a first-class agent tool, not a separate admin console.
Threaded comments visible
The conversation around a wiki page is part of the answer — the agent surfaces threaded comments alongside the canonical text.
Soft-delete with admin restore
delete_wiki is soft and restorable by admin — the confirmation prompt makes that explicit so deletions aren't a one-way door.
RubyLLM model tiering
Full-body search runs on small tier; summarization on standard; drafting on standard. Cost per query stays bounded at large wiki volumes.
INDUSTRY FIT
Industries where wiki knowledge moves the most weight
Wikis Agent shines where institutional knowledge changes weekly and search is the difference between finding and rebuilding.
Technology
Runbooks, ADRs, and on-call playbooks searchable across body content — fewer "rebuild from scratch" incident retrospectives.
Healthcare
Clinical reference and operational wikis surface the current version with attribution — auditors see who reviewed what when.
Financial Services
Internal procedure wikis with strict draft/published states; FINRA examiners see exactly what was authoritative on any given date.
Manufacturing
Engineering and quality knowledge bases searchable by line, station, and material — supervisors find the right page on a kiosk in seconds.
Professional Services
Methodologies, playbooks, and project archives surface across body content — consultants don't reinvent the wheel each engagement.
Public Sector
Policy and procedure wikis with admin-only status filters; within the FedRAMP-eligible boundary, no public-internet AI tool indexing.
WHY MANGOAPPS WINS
An embedded wikis agent beats a Confluence AI, a Glean bolt-on, or a custom search build on every axis
The argument knowledge owners, IT, and compliance all share — and the one a horizontal AI or a search-only vendor structurally cannot answer.
Cheaper than the alternatives
No Confluence AI / Notion AI / Guru per-seat fee, no Glean enterprise contract, no custom search build, no extra KM headcount sweeping for stale pages.
More secure
Three admin-only writes, confirmation-gated; status filter admin-only; every action logged through AiApiLog. Stays inside the tenant.
Easier to deploy
Already deployed if Wikis is enabled. Turn the agent on and full-body search / version history / threaded comments work the same day.
Easier to use
"Find the deploy runbook" / "who last edited the comp guidance" / "archive the old expense policy" — one prompt each.
Easier to manage
Per-business status workflows, admin-only filters, and retention rules sit in the same admin console as every other app's settings.
Easier to extend
New status transitions, new comment thread types, new version-history signals ship as tools — the agent picks them up the same release.
AI is actually better
A vendor or generic AI can search titles. Only Wikis Agent can also search the full body, scope by admin-only status, surface version history and threaded comments, and gate writes through confirmation.
At our head office within HR, marketing, and finance, we use ChatGPT quite a bit, and MangoApps AI Helper is a useful tool for us. As I go around to the stores, I’ve been showing them how the AI Intranet Helper can find things and answer plain language questions about our resources, and they’re quite excited about that.
Alison van Zijl
Head of Human Resources
Full House
Customer Success
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Frequently Asked Questions About Wikis Agent
10 tools — 7 reads and 3 admin writes. Reads include search_wikis (title + description + body), get_wiki_content, get_wiki_details, list_wikis, get_wiki_versions, get_wiki_comments, get_wiki_stats. Writes (admin only, all gated) are create_wiki, update_wiki_status, delete_wiki.
All 3 admin writes are in RISKY_TOOLS and require explicit user confirmation. create_wiki creates drafts only. delete_wiki is a soft-delete and restorable by an admin. The permission check rejects non-admin users before the model ever sees the tool as available.
Yes. search_wikis searches title, description, AND body content. Optional tag and status filters narrow the scope (status filter is admin-only — non-admins can only see published wikis).
get_wiki_versions returns version numbers, change types, authors, and dates from the wiki's audit log. The default limit is 10 versions; the tool is read-only. Pair with get_wiki_comments to surface institutional context that lives in threaded discussion.
Body-search hit rate (vs title-only match), wiki re-author rate (duplicates created on already-covered topics should fall), version-history adoption, stale-wiki burndown per quarter, and admin-write override rate (cancelled vs confirmed). Compare against your pre-agent baseline.
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