Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/unifapi-agent/agents/linkedinnpx skills add unifapi-agent/agents --skill linkedingit clone --depth 1 https://github.com/unifapi-agent/agentsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00115 | $0.01842 |
| Opus 5 | $0.00057 | $0.00921 |
| Sonnet 5 | $0.00023 | $0.00368 |
| Haiku 4.5 | $0.00012 | $0.00184 |
Grade A, and why
linkedin scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The deterministic read path for public LinkedIn data through UnifAPI. This is
a Data Skill: it does not run a marketing job on its own — it names the
concrete linkedin/... operations, response shapes, and gotchas so any
B2B-first workflow (account research, news signals, buying signals, competitor
profiling) reads from one known recipe instead of rediscovering the surface each
time.
Read-only — eyes, not hands. It researches public LinkedIn data and returns cited records; it never connects, messages, or applies, and UnifAPI never holds LinkedIn credentials.
Use the unifapi skill for live evidence
Connect once through the shared unifapi skill (OAuth MCP), then call the
operations below. Companies are keyed by their public {slug} (the vanity
segment of the company URL) and people by their public {username} — read
both from the LinkedIn URL, not a numeric id. Keep any billing metadata so the
output can state record cost.
Response contract
Single-entity endpoints return the object in data:
{
"request_id": "unif_...",
"data": {},
"billing": { "records_charged": 1, "balance_remaining": 99 }
}
List endpoints return an array in data plus pagination:
{
"request_id": "unif_...",
"data": [],
"pagination": { "has_more": false, "next_cursor": null },
"billing": { "records_charged": 1 }
}
When pagination.has_more is true, pass pagination.next_cursor as the next
request's cursor. Always preserve billing when reporting cost.
Core operations
| Need | Operation |
|---|---|
| Company page | linkedin/companies/{slug} |
| Company headcount signal | linkedin/companies/{slug}/job-count · .../jobs |
| Company people | linkedin/companies/{slug}/people |
| Member insights | linkedin/companies/{slug}/member-insights |
| Company posts | linkedin/companies/{slug}/posts |
| Person profile | linkedin/users/{username} · .../about · .../experience |
| Person reach | linkedin/users/{username}/follower-count |
| Person posts / reactions | linkedin/users/{username}/posts · .../reactions |
| Search people | linkedin/search/people (?title=¤t_company=&industry=) |
| Search jobs / posts | linkedin/search/jobs · linkedin/search/posts |
| Job / post by id | linkedin/jobs/{id} · linkedin/posts/{id} (.../comments) |
| Resolve a geocode / industry | linkedin/search/locations · linkedin/search/industries |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 149 lines · 115 tokens per session scan A 05f0d67eec5f
linkedin is a skill published in the GitHub repository unifapi-agent/agents (557 stars, last pushed 2mo ago), licensed MIT. It adds 115 tokens to every session and 1,842 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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