# PersonalKnowHow

> Live public demo: query one person's learning and work history as a knowledge graph via MCP.

- name: io.github.Georgi-Petkov/personalknowhow
- version: 1.0.0
- connection class: R0 (autonomous)
- trust: 94/100
- quality: 86/100 (good)
- owner: not claimed
- descriptor: https://api.protogrid.dev/v1/servers/io.github.Georgi-Petkov%2Fpersonalknowhow
- tools: https://api.protogrid.dev/v1/servers/io.github.Georgi-Petkov%2Fpersonalknowhow/tools

**An agent can connect right now, no human step.** Remote endpoint, no authentication, reachable on the last probe.

## Connection (mcpServers)

```json
{
  "mcpServers": {
    "personalknowhow": {
      "type": "http",
      "url": "https://personalknowhow-demo.kxtwrdzt6g.workers.dev/mcp"
    }
  }
}
```


## Trust

- hygiene: 100
- liveness: 100
- freshness: 85
- provenance: 90
- drivers: +repository +namespace-matches-repo +website +reachable +uptime-99% ~updated-43d-ago
- Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed.

## Quality 86/100 (good)

### protocol: 88 (weight 25)

- pass `protocol.modern`: supports 2026-07-28 (server/discover)
- pass `protocol.stateless`: answers without a session
- pass `protocol.transport`: streamable HTTP
- warn `protocol.list_ttl`: tools/list declares ttlMs 0, so clients re-fetch it on every use

### authorization: n/a (weight 15)

- n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth
- n/a `auth.secret_in_url`: no templated URL

### tool hygiene: 79 (weight 30)

- pass `tools.descriptions`: every tool has a description
- warn `tools.description_length`: 2 tools have descriptions over 1,024 characters, which crowds the context
- pass `tools.schemas`: every tool has an object input schema
- pass `tools.annotations`: 4 of 4 tools declare readOnlyHint or destructiveHint
- fail `tools.directory_hints`: no tool declares all four of readOnlyHint, destructiveHint, idempotentHint and openWorldHint; missing: query_knowhow (destructiveHint, idempotentHint, openWorldHint); related_entries (destructiveHint, idempotentHint, openWorldHint); skill_evidence (destructiveHint, idempotentHint, openWorldHint); …
- pass `tools.token_cost`: about 1,281 tokens to load every tool
- pass `tools.api_dump`: tools are not a one-to-one API dump

### stability: 100 (weight 15)

- pass `stability.changes`: no tool changes in 30 days
- pass `stability.rug_pull`: no tool changed its meaning under the same name

### dependencies: n/a (weight 15)

- n/a `deps.known_vulns`, `deps.mcp_sdk_version`, `deps.resolvable`: no npm or PyPI package

- tools: 4, about 1,281 tokens to load them all
- tool set hash: 17e5ffed785963e0ffaf891f76671aef
- badge: [![protogrid quality](https://protogrid.dev/badge/io.github.Georgi-Petkov/personalknowhow.svg)](https://protogrid.dev/servers/io.github.Georgi-Petkov/personalknowhow)
- Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed.

### Tool changes

_No tool definition changes recorded._

## Remotes

- https://personalknowhow-demo.kxtwrdzt6g.workers.dev/mcp (streamable-http, auth none, reachable true, uptime30d 0.99159664)

## Packages

_none_

## Tools (4)

- `list_by_type`: Returns the COMPLETE, exact set of entries for one type, with no similarity ranking, no relevance cutoff, and no cap on count. Use this instead of query_knowhow whenever the question requires an exhaustive or countable answer ('list all my certifications', 'how many courses have I completed'). Deterministic ordering (sorted by label) -- repeated calls with the same type return the same list in the same order.
- `query_knowhow`: Search this person's real, grounded skills/experience graph for a topic using semantic search. Returns only entries with real evidence -- never guesses. Every entry here represents something actually done or completed (project, certification, position, course, or education) -- this public dataset never includes saved-but-not-worked jobs or applications. This is SEMANTIC search ranked by relevance and capped at 10 results -- it is NOT exhaustive. For 'list every X' or 'how many X' questions, use list_by_type instead -- it returns the complete, uncapped set with no similarity ranking involved. Clearing the similarity floor means 'closest available match', not 'confirmed match' -- read each result's actual label/description/type before citing it as evidence for the specific topic queried. Each result also carries source_url/captured_at/provider (the real evidence behind it, when available) and source_note (explaining why not, when the underlying source has no link) -- use these to answer a disputed claim with actual backing evidence rather than just the description text. Embeddings can rank a topically-adjacent-but-wrong entry above the floor (e.g. a course on a different cloud data-warehouse tool, or a different framework in the same category) for a term it isn't actually about; if a result isn't genuinely on topic, treat the query as unmatched rather than reporting it as a match. For 'what else is connected to this' or 'what shares a skill/provider with this specific entry' questions, call related_entries with a result's id instead of re-querying by topic.
- `related_entries`: Given an entry id (from a prior query_knowhow or list_by_type result), returns other entries that share at least one tag or the same content provider -- the only two relationships this corpus currently tracks (there is no 'led to' or 'used in' relationship here, only shared tag/provider). This is NOT a similarity or relevance judgment -- two entries sharing a broad tag (e.g. both tagged 'data-science') can be quite different in substance; read each related entry's own label/type before treating it as meaningful. Each group is capped at 15 entries, sorted by label, with the true total count shown separately so you know if results were truncated -- call list_by_type on that type if you need the full set. Useful for 'what else is connected to X' or 'what did they do that relates to this specific course/certification/endorsement' -- questions query_knowhow's independent similarity search can't reliably answer, since two entries can be genuinely related without their description text reading alike (e.g. a course title and an endorsement phrase for the same skill, worded completely differently).
- `skill_evidence`: Given an exact tag/skill (e.g. 'docker', 'gcp'), returns EVERY entry with that tag, uncapped, grouped by type with a real count per type. Unlike related_entries (capped at 15, requires a starting entry id) or query_knowhow (semantic, ranked, may over- or under-include), this is an EXACT tag match against every entry -- the right tool for 'how many X have I completed/done' or 'do I have any real evidence for X at all'. Tags are exact strings from a prior list_by_type/related_entries/query_knowhow result's tags array -- this is NOT semantic search; a tag never assigned during ingest returns found:false, try query_knowhow instead. Each type's entries sort by captured_at ascending (oldest first); entries with no captured_at are moved to the end and counted in undated_count, never silently sorted as if their date were known.