agentleFS
Sign inStart free
adriano-labsadriano-labs/applyarc-claude-plugin/skills/offer-negotiation/SKILL.md

offer-negotiation

Skill0 starsChanged 29 days agoMITView on GitHub

Helps the user understand and negotiate a job offer with ApplyArc. Breaks down the full package, sets a walk-away point and one clear counter, drafts the negotiation email and call script, and role-plays the call. Use when the user says "I got an offer", "should I accept", "negotiate my salary", "counter offer", "they asked my salary expectations" or "compare two offers". Uses the job in the user's ApplyArc tracker when connected.

1 other project uses a version of this.

Adopted by

Most recently taken up by

  • Other versions1 project uses a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 1

    1. ficilcom/otame4-work-skills★ 3same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository6 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 4 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Honesty: Do not invent competing offers or fake deadlines.

    line 22
  2. Very specific:

    Find the job: Call list_my_jobs with status: "offer", or ask for the company and role.

    line 30
  3. Distinctive:

    Ask what matters beyond money (flexibility, title, learning, start date).

    line 37
  4. Distinctive:

    Close: When the user accepts, confirm the final terms in writing and offer to tidy other applications in the tracker (pipeline-coach).

    line 50
  5. Distinctive:

    Put each offer in a table: base, bonus, pension, holiday, commute or remote, growth, team, and the user's top two priorities.

    line 55

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Offer negotiation

Help the user get a fair offer without damaging the relationship. Uses the ApplyArc MCP server (applyarc) for the tracked job and the salary-negotiation tool.

Why this shape: most employers expect a respectful counter, and a single, well-reasoned ask anchored in evidence works better than several small ones.

Ground rules

  1. No invented numbers. Salary data comes from the user, the posting, or sources they paste. Anything from your background knowledge is labelled "From memory, may be out of date" and never presented as market fact.
  2. The user decides. Lay out options and trade-offs; do not pressure them to accept or decline.
  3. Honesty. Do not invent competing offers or fake deadlines.
  4. No legal or tax conclusions. Point to official sources (for example GOV.UK) and suggest checking with an adviser for contracts.
  5. Ask before spending. generate_for_job uses one AI generation.
  6. British English. No em dashes.

Workflow

  1. Find the job. Call list_my_jobs with status: "offer", or ask for the company and role. If the job is not at offer, offer update_job_status.
  2. Capture the full offer. Base, bonus, equity, pension contribution, holiday, notice period, start date, hybrid or remote terms, location, probation, benefits, and any deadline. Ask for what is missing.
  3. Know the user's numbers. Current package, target, and walk-away point. Ask what matters beyond money (flexibility, title, learning, start date).
  4. Generate the plan. With the user's yes, call generate_for_job with toolId: "salary-negotiation", putting the offer details, target and priorities in notes.
  5. Pick one counter. Base it on evidence: the posting's range, the role's scope, the user's specific strengths from get_my_profile. Prefer one main ask plus one fallback (for example sign-on bonus, extra holiday, earlier review).
  6. Draft. A short, warm email: thanks, enthusiasm, the ask with one or two reasons, openness to talk. And a 60-second call script with responses to "that's our best offer" and "what's your number?".
  7. Rehearse. Offer to play the hiring manager. After the role-play, quote what worked and one line to tighten.
  8. Close. When the user accepts, confirm the final terms in writing and offer to tidy other applications in the tracker (pipeline-coach).

Comparing offers

Put each offer in a table: base, bonus, pension, holiday, commute or remote, growth, team, and the user's top two priorities. Highlight the trade-off, then let the user choose.

Salary expectations early in the process

Suggest asking for the budgeted range first. If pressed, give a range whose bottom is a figure the user would be happy with, tied to the role's scope.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free