linkedin-mcp-server is a local MCP server that gives compatible AI assistants access to LinkedIn through a logged-in browser session. Agents can use it to inspect profiles and companies, search jobs, retrieve job details, and manage certain LinkedIn interactions. The catalogue add-ons operate this server and expose its LinkedIn workflows to agents.
Borrowing it
Nothing to install: this file belongs to stickerdaniel/linkedin-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/stickerdaniel/linkedin-mcp-server/main/.agents/skills/3-verify-pr-fix/SKILL.mdgit clone --depth 1 https://github.com/stickerdaniel/linkedin-mcp-serverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/stickerdaniel/linkedin-mcp-server/3-verify-pr-fix)<a href="https://agentmods.dev/skills/stickerdaniel/linkedin-mcp-server/3-verify-pr-fix"><img src="https://agentmods.dev/badge/skills/stickerdaniel/linkedin-mcp-server/3-verify-pr-fix/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/stickerdaniel/linkedin-mcp-server/3-verify-pr-fix"><img src="https://agentmods.dev/badge/skills/stickerdaniel/linkedin-mcp-server/3-verify-pr-fix.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 76 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- medium Data Exfiltration · line 109 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 119 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
What 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 5.1 | $0.00032 | $0.02277 |
| Opus 5.5 | $0.00013 | $0.00911 |
| Sonnet 5.5 | $0.00006 | $0.00455 |
| Haiku 4.5 | $0.00003 | $0.00228 |
Grade A, and why
3-verify-pr-fix scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 24d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -D /tmp/verify-pr-$PR-headers -X POST http://127.0.0.1:$PORT/mcp \ Copies of this mod
5 near-identical copies found in the catalogue:
- 3-verify-pr-fix — 100% identical, 182 lines differ
- 3-verify-pr-fix — 100% identical, 182 lines differ
- 3-verify-pr-fix — 100% identical, 182 lines differ
- 3-verify-pr-fix — 100% identical, 182 lines differ
- 3-verify-pr-fix — 100% identical, 182 lines differ
How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Verify a candidate PR
Review the packet, the candidate diff, and relevant tests. Live comparison against a captured baseline is optional. No edits, no merges, no pushes.
1. Resolve the PR and its linked issue
PR=$(echo "$ARGUMENTS" | sed -E 's|.*/||; s|#||g' | grep -oE '^[0-9]+' | head -1)
[ -z "$PR" ] && { echo "Invalid input: '$ARGUMENTS'. Pass a PR number or URL." >&2; exit 1; }
REPO=stickerdaniel/linkedin-mcp-server
gh pr view $PR --repo $REPO --json title,body,baseRefName,headRefName,headRepositoryOwner,mergeable,mergeStateStatus,additions,deletions,changedFiles,maintainerCanModify,statusCheckRollup
Extract the linked issue number from the PR body (Closes #, Fixes #, Resolves #, or plain #N). Call it ISSUE. If multiple, ask which one is the verification target.
Read that issue's packet and comments.
2. Packet, diff, and tests
This path does not need /tmp/repro-issue-$ISSUE-main.json. Absence of a local baseline limits the live branch, not the whole PR verdict. Do not create fake success or failure files.
gh pr diff $PR --repo $REPO
gh pr view $PR --repo $REPO --json files --jq '.files[].path'
Hard flags (any one downgrades a clean live pass to concerns):
- Locale-dependent detection:
== "Connect",in ["Pending", "Follow"],contains("1st"),aria-label="..."with translated text. Attribute presence is the locale-independent signal. - LinkedIn class-name selectors:
.entity-result__item,.artdeco-button__text. Minimal generic selectors only (a[href*="/jobs/view/"]). - Multiple navigations behind one
PERSON_SECTIONS/COMPANY_SECTIONSentry. - Missing tests beside the canonical owner from
docs/linkedin-architecture.md.
A supplied capture or regression fixture can support a before-and-after claim within its scope. Protocol or startup failures are execution limits, not a pass.
This step is complete when the report can say whether the diff addresses the packet at this SHA, which audit flags apply, and whether a live comparison is still needed.
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.
- 24d ago Changed c5fd0b91e6cf
- 1mo ago Changed · -38 lines · -45 tokens per session 3495c70a3f0c
- 1mo ago Changed 281dc667707c
- 1mo ago First seen · 201 lines · 77 tokens per session scan A 156cac8c102f
3-verify-pr-fix is a skill published in the GitHub repository stickerdaniel/linkedin-mcp-server (4,014 stars, last pushed yesterday), licensed Apache-2.0. It adds 32 tokens to every session and 2,277 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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gitnexus-impact-analysis
Use when the user wants to know what will break if they change something, or needs safety analysis before editing code. Examples: "Is it safe to change X?", "What depends on this?", "What will break?".
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Use when the user wants to rename, extract, split, move, or restructure code safely. Examples: "Rename this function", "Extract this into a module", "Refactor this class", "Move this to a separate file".
liveagent-code-review
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