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Add a trusted person to your knowledge base: preview their identity from an X handle, blog URL, or canonical ID, then ingest their X timeline, blog archive, and GitHub into searchable local storage.

Instructions

Add a person to your knowledge base as an Oracle — a trusted source OPYT deep-ingests (their X timeline + Substack/blog archive + GitHub) and roots trust on. This is the atom-KB "add a person" — the only one: the old vault-era add_person tool, which wrote the legacy vault and couldn't admit a Substack/blog-rooted person, is retired.

SAFE, TWO-PHASE — always preview before you ingest: • FIRST call with confirm=False (the default) → a PREVIEW. It resolves reference and returns who they are (name, bio, followers) — or, if already known, their roster entry — and writes NOTHING. Read it back to the user to confirm it's the right person. If the reference doesn't resolve you get unresolved and there's nothing to confirm. • THEN, once the user agrees, call again with confirm=True → runs the full ingest and writes to the store. Never call confirm=True without showing the preview first — the guard is against ingesting the WRONG PERSON, which no later call undoes.

reference is polymorphic: an X @handle ("@karpathy"), a Substack/blog/site URL ("https://simonwillison.net"), or a canonical_id from oracle(action='screen') (to promote a below-the-cut candidate). To add someone by NAME, YOU resolve the name → their @handle or URL first (your own knowledge / a web search), then pass that — there is no name-search endpoint.

TWO windows, asked separately, because they answer to different constraints: • x_lookback — "6mo" (default) / "1yr" / "2yr". Hard-capped at 2 years whatever you pass. ASK the user before a confirm=True; the ~6-month default silently leaves most of a prolific account's history out. For someone ALREADY on the roster, "since_last" pulls only what is new since their last pull — the cheap top-up, roughly one request for a few days' gap. Reach for it when the user says "update" or "catch up", not "add". • web_lookback — "1yr" / "2yr" / "5yr" / "all" (default). A durable archive, so it already pulls everything. Pass it only to NARROW. A single shared window would be wrong for one of the two by construction — it either over-pulls X or truncates the archive. The result echoes the windows that actually ran (including the X clamp) under lookback — TELL the user how far back you pulled.

Reading the result — do not report ingested as if it were the whole story: • ingested counts sources that actually ingested; blocked counts sources where the host stopped us (Cloudflare, a truncated archive). A blocked source wrote nothing and is retried on the next run — say so plainly ("their Substack was blocked, nothing was saved, it'll retry") rather than implying it worked. errors is the "something is wrong, worth a look" bucket. • atoms_added vs dispatched: lookback/limit bound posts ATTEMPTED, not atoms saved, so these two diverge whenever posts are paywalled or fail the quality gate. If atoms_added is much smaller, tell the user the number they actually got. • producer_failed > 0 means posts vanished mid-run — mention it; nothing else records it.

The result may ask you to do something — check for followup. A confirm=True result carries one, and acting on it is how this tool finds a person's blog / YouTube / podcasts at all. OPYT's four probes are deterministic (X bio, Substack convention, GitHub, Semantic Scholar); the open-web step is YOURS, because you have web search and OPYT would otherwise pay a second model for a worse version of it. So: run the search it describes, then call this tool AGAIN with the same reference, confirm=True, and the URLs in extra_source_urls. Send everything plausible — you do NOT need to verify ownership, because the trust graph re-checks every URL and rejects what it cannot corroborate. A URL you drop is invisible; a URL it rejects lands in needs_review.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
forceNore-run DISCOVERY from scratch, ignoring the cached result. Discovery is cached for a person whose X profile is unchanged, because identity is stable while their CONTENT is not — a normal re-add should not re-derive who they are. Pass this when the user says their sources look wrong or incomplete and re-adding did not help. The cache key is their display name plus declared links, so a source they created after the last run leaves it identical and only this gets past it. Costs a full probe walk; do not pass it by default.
confirmNoFalse (default) = preview only, no writes; True = run the ingest.
referenceYesan X @handle, a Substack/blog URL, or a canonical_id.
x_lookbackNowindow for the X timeline — "6mo" | "1yr" | "2yr" (default 6mo).
web_lookbackNowindow for the Substack/blog archive — "1yr" | "2yr" | "5yr" | "all" (default all). Narrows only.
extra_source_urlsNohome/channel pages YOU found by web search (see `followup`). They enter as low-confidence candidates and are trust-checked like any other source — never trusted on your say-so. Individual posts/videos are dropped; send homes.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals the safe two-phase write behavior, the 2-year hard cap on x_lookback, the fact that blocked sources write nothing and are retried later, the divergence between atoms_added and dispatched, and the trust-re-checking of extra_source_urls. This goes well beyond what the schema alone conveys.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but well-structured with headers and bullets, and it front-loads purpose and safety workflow. Each section addresses a distinct operational concern—preview/confirm, lookback windows, result interpretation, and followup—so the length is proportional to the tool's complexity rather than padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a six-parameter mutation tool with no annotations, the description covers the entire call lifecycle: reference resolution, preview/confirm behavior, lookback semantics, result-field interpretation, and the followup/extra_source_urls loop. The output schema supplies the raw return shape, and nothing an agent needs to invoke this tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds significant meaning: it explains reference's polymorphic forms with concrete examples, notes that name lookup must be resolved externally, introduces the since_last x_lookback value, warns about the hard cap, and clarifies that extra_source_urls are low-confidence candidates that must be home pages, not individual posts. This substantially enhances the parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening sentence names a specific verb and resource: add a person to the knowledge base as an Oracle, with the effect of deep-ingesting their X timeline, Substack/blog archive, and GitHub. It also explicitly distinguishes itself from the retired add_person tool and claims to be the only atom-KB add-person tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives an explicit call pattern: confirm=False preview first, then confirm=True only after user agreement, and says never to call confirm=True without showing the preview. It also explains when to use the since_last window ('update'/'catch up', not 'add'), when to narrow web_lookback, and how to act on the followup, leaving no ambiguity about when and how to use the tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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