Update to Tavily

{
  "description": "Fill in a company, person, or organization for a CRM from the web, using Tavily, including a CSV of rows the user already has. Identifies the right entity when others share the name, then fills the fields from authoritative sources. Use when the user wants to enrich an account, a spreadsheet, or a pasted list of known names, or says \"enrich\", \"CRM\", or \"who is\". For discovering matches use tavily-list. For a deep comprehensive report use tavily-research.\n",
  "included_files": [],
  "name": "tavily-entity",
  "skill_md_contents": "---\nname: tavily-entity\ndescription: |\n  Fill in a company, person, or organization for a CRM from the web, using Tavily, including a CSV of rows the user already has. Identifies the right entity when others share the name, then fills the fields from authoritative sources. Use when the user wants to enrich an account, a spreadsheet, or a pasted list of known names, or says \"enrich\", \"CRM\", or \"who is\". For discovering matches use tavily-list. For a deep comprehensive report use tavily-research.\nallowed-tools: Bash(tvly *)\n---\n\n# Tavily entity\n\nResolve one entity and return a CRM record. The name is not the identity.\nConfirm which entity it is, then fill the record from authoritative sources.\nEvery value comes from a page you read. An empty field stays empty.\n\nSearch and extract as `tavily-search` describes; load it only if it isn't\nloaded yet. To discover new matches use `tavily-list`; for a deep report use\n`tavily-research`.\n\n## Identify the entity first\n\nPeople and companies share names. A record that mixes two of them is worse\nthan an empty one. Isolate a single entity before you fill any field.\n\n1. Take the type (company, person, or organization) and every identifier the\n   user already gave: a domain, a city, an employer, a title, a product.\n2. Search the name and look for other entities that use it. A common name, a\n   name that is also a product or a place, or a person with a common name is a\n   collision until you prove otherwise.\n3. You have the right entity only when two identifiers agree. For a company,\n   the name plus its own domain. For a person, the name plus an employer, a\n   location, or a profile they control, and the organization on that profile\n   has to match. One page that mentions the name is not identification.\n4. If more than one entity still fits, stop and return the candidates. Do not\n   pick the one with more results, and do not copy a field from one candidate\n   onto another.\n5. Put a stable identifier, the domain or the employer, into every later\n   search, not the bare name.\n\n## Read authoritative sources\n\nFill a field from the page that owns the fact. Extract that page. A snippet is\nnot enough for a number.\n\n- The entity's own site, an official profile, and a filing or registry come\n  first for facts the entity publishes: what it is, where it is, who leads it,\n  what it sells. For a person, the employer's team page or a profile the person\n  controls comes before a people-search site.\n- A directory, a data broker, or a roundup is a lead to that page. Use it as\n  the source of a field only when no authoritative page states the fact, and\n  say so in the source note.\n- When two authoritative pages disagree on a number, keep the more direct one\n  and record the other in the source note. Do not average them.\n- Include a published email or phone number only when a page shows it.\n\nExtract the pages that own the fields you need in one call. Search for recent\nnews, with the domain or employer in the query, only when the user wants recent\nsignals or a full record.\n\n## A CSV of known rows\n\nWhen the user already has the entities, in a file or a pasted table, enrich\nthose rows. Do not go looking for new names.\n\n1. Read the rows and count them. Use the fields they named. If they did not\n   name fields, ask once, then use the same fields on every row.\n2. Above 25 rows, tell them the count and the fields and wait for a go-ahead.\n3. For each row, follow Identify the entity first and Read authoritative\n   sources. A row you cannot isolate stays unresolved: blank new fields, a note\n   on what collided, and no guessed values.\n4. Write the original columns plus the new fields, a source for each new\n   field, and a status of `filled` or `unresolved` to\n   `{name}-enriched-{YYYY-MM-DD}.csv`. Use a CSV writer.\n\nThe CSV is the result. In the reply, give the number filled, the number\nunresolved, and the path. Do not paste a record per row.\n\n## Output\n\nWhen the user asked specific questions, answer those in the reply, with a source\nfor each value, and skip the template. For a full record, use this:\n\n```markdown\n# {Name}\n\ntype: company | person | organization\nidentified by: {domain, employer, or other stable identifier}\nas_of: {YYYY-MM-DD}\n\n| Field | Value | Source |\n|---|---|---|\n| website | | |\n| description | | |\n| industry | | |\n| headquarters | | |\n| founded | | |\n| employees | | |\n| funding | | |\n| revenue | | |\n| linkedin | | |\n\n## People\n| Name | Title | Source |\n|---|---|---|\n\n## Recent signals\n- {YYYY-MM-DD}: {fact} — {url}\n\n## Unknown\n- {field}: {what you tried}\n```\n\nFor a person, the field rows are title, organization, location, and profile URL,\nand People appears only when the user asked for related people. Drop a field\nrow that does not apply to this type. A field that applies and could not be\nfilled stays in the table with a blank value and a line under Unknown.\nDescription is one or two sentences grounded in the about page or profile.\nRecent signals are at most five dated items: funding, a launch, a leadership\nchange, hiring. Omit a section that has no rows.\n\nWhen you cannot pick one entity:\n\n```markdown\n# {Query}\n\n| Name | Website | What separates it from the others |\n|---|---|---|\n```\n"
}