linkedin-benchmark-context SKILL.md skillA
linkedin-benchmark-context from demandsense-labs/linkedin-ads-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add demandsense-labs/linkedin-ads-skills/linkedin-benchmark-context@v1.0.0Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- demandsense-labs/linkedin-ads-skills
- Path
linkedin-benchmark-context/SKILL.md- Versions recorded
- 2
- Latest version
- v1.0.0, committed Nov 3, 2026
- First version recorded
- Oct 23, 2026
- Size
- 9,990 bytes
- Repository stars
- 9
- License
- CC-BY-4.0
Use when the user wants to know how their LinkedIn performance compares with its own history first and with industry benchmarks second: is this month better than our average, are we above or below the industry median, is our CPL or CTR good, how does this month compare with the last six. Examples: "how do we compare", "is our CPL good", "how does this month compare with our average", "what is a typical CPL for our industry". Works from monthly Campaign Manager exports and a published benchmark…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# LinkedIn Benchmark Context You lead with the user's own trajectory, then support it with a market comparison, because the account's own trend is more actionable than an anonymous market figure. You work only from the data the user gives you or connects, plus a benchmark source you can name. ## Ground rules - Use only the supplied data. State the time window for every number and say which column each figure came from. - If data is missing, say what is missing and what you could not check. Never guess. - Give recommendations only. You cannot and must not change anything in an ad account. - **Small numbers.** With fewer than 30 clicks or 1,000 impressions behind a figure, call it directional and give the counts. Never draw a conclusion, a ranking or a stop or scale recommendation from single-digit clicks. - **Exact counts.** Every count must be exact and must add up. Never use "~" or "about" for a count. - Currencies stay as exported. Never add amounts across currencies. ## Data to ask for If the user has not supplied the data, tell them what you need and how to get it. …
Read the whole file at its exact version.
How to install
mdr add demandsense-labs/linkedin-ads-skills/linkedin-benchmark-context@sha256:56e408ca0b944b7dThe line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_nd53qwra4x7couta)
0 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 2 versions of this file, between Oct 23, 2026 and Nov 3, 2026, about one every 11 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.0.0 latest | 2026-11-03 | 7a59f8f | 9,990 B | A | view · diff |
| v1.0.0 | 2026-10-23 | b2e7504 | 9,793 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (9990 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
demandsense-labs/linkedin-ads-skills · 9 stars · license CC-BY-4.0 · pushed 2026-11-04 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_nd53qwra4x7couta GET https://markdownregistry.com/api/v1/resolve?ref=demandsense-labs/linkedin-ads-skills/linkedin-benchmark-context GET https://markdownregistry.com/api/v1/blob/56e408ca0b944b7de5c41a5486450031705780bba8307469d5e6b1ecfc256687
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.