getedgehq People Search
Produce an auditable shortlist without pretending the skill itself grants LinkedIn data access.
Choose the data mode
Use the strongest mode already available: provided CSV/profiles/export; public web search; an authorized authenticated session; or a connected provider such as HarvestAPI or Apify. If no discovery source is available, return a normalized search plan, ready-to-run filters, and an input template. Never fabricate profiles.
Workflow
- Translate the request into the canonical schema.
- Separate hard requirements from ranking preferences. Treat vague criteria as preferences unless explicitly mandatory.
- State the selected mode and its coverage limits.
- Map canonical filters to provider fields and disclose every applied, approximated, dropped, or unsupported filter.
- Run the cheapest useful canary before a paid/full search. Stop on invalid, silently empty, or off-target results.
- Deduplicate by stable profile URL, then normalized name plus current company.
- Rank against the original brief, preserve evidence URLs, and distinguish sourced facts from inference.
- Return the shortlist, search recipe, caveats, and highest-value refinement.
Boundaries
- A skill is orchestration, not a data license. Never imply built-in LinkedIn access.
- Never expose, embed, or persist provider credentials.
- Make the cost-bearing mode clear before paid search; prefer previews and staged expansion.
- Never interpret zero results as no matching people until request validity and filter support are checked.
- Do not send connection requests or messages without separate authorization.
For adapter behavior and result contracts, read references/provider-contract.md.
Deterministic runner
Use scripts/people_search.py for plan-only, CSV import/ranking, and provider execution. Provider credentials must enter through the named environment variable at process scope; never pass a token as an argument.
Hard filters are field-scoped: --locations matches the location field only, --titles the current_title, --companies the current_company, --industries the industry. Only --must-keywords and --exclude-keywords scan several fields, and those are reported as approximated. Exclusions are first-class: --exclude-companies, --exclude-titles, --exclude-keywords, --exclude-profile-urls.
Every requested filter appears exactly once in filters, sorted into applied, approximated, dropped, or unsupported, with the fields it matched and the reason for its status. A filter whose target field is missing from the data is dropped and not enforced, so the result set is wider than the brief and says so. Report that ledger to the user; do not restate the brief as if all of it ran.
Provider runs are staged. --provider-run canary is the default: a preview request capped by --canary-limit (5), never a complete result set. --provider-run full sends preview: false and the real --limit, and requires --max-cost-usd. Add --cost-per-result-usd so the cap is checked before the request instead of after the invoice; without it cost.cap_enforced is false. A provider-reported cost above the cap comes back in warnings.
Read ok before results. On success ok is true, results_valid is true, and results is a list that may legitimately be empty, in which case zero_result_note and diagnostics.rejected_by_filter explain what removed the candidates. On failure the runner exits 2, writes the reason to stderr, and emits ok: false with results: null, never an empty list, so a missing credential or an HTTP 402 cannot be read as "there are no such people".