agentsclimarketplace

Consult market

Skill Timelnapp/skills/skills/consulting-os/consult-market

6 SKILLs to improve Claude Code memory, derived from Timeln's second brain capability to remember everything.

Install
npx -y skills add Timelnapp/skills --skill consult-market

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Trigger on "find similar clients", "lookalike accounts", "who else would buy this", "market research for this use case", "expand after a win", "consult market", "cos market", "/cos-market". Manual seed (industry + size + use case) → ranked top-5 lookalike target list with why-it-fits rationale and verified-or-labeled contacts. Uses timeln-find; optional Apollo/Clay/Exa. NOT outreach (use consult-pursue), NOT framing (use consult-frame).

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

4.6 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it

Consult Market -- Lookalike Target List

After a win, find the next 5 companies in the same industry and size who would buy the same use case. One job: a ranked, sourced target list — not outreach, not a pitch.

Inputs (manual — ask if missing)

InputRequiredNotes
Industry / verticalyese.g. "regional telco", "DTC supplements"
Company size bandyesrevenue, headcount, or both — e.g. "200–2,000 staff"
Use caseyesone line on what was sold/won — the buyer's reason to care
Region / geographyoptionaldefault: same region as the win
Exclusionsoptionalthe won client, named competitors, do-not-contact list

No engagement-passport.yaml needed. If the user points at a won proposal pack, use it only to sharpen the use-case one-liner — do not require it.

Data sources (degrade gracefully)

  1. timeln-find — analogous engagements / accounts already in memory. Run first; cite titles only.
  2. Web + Exa — public firmographics, recent buying signals (funding, hires, product launches, regulatory pressure, RFPs). Every company → source URL.
  3. Apollo / Clayonly if connected — firmographic filtering and verified contacts. If absent, skip silently; do not block.

If Timeln MCP is unavailable, note timeln skipped — no MCP and continue with web + Exa only. Never fabricate memory results.

Workflow

  1. Confirm the three required inputs; restate the use case in one buyer-centric sentence.
  2. timeln-find for accounts/engagements that match the vertical + use case.
  3. Web/Exa (and Apollo/Clay if present) to build a candidate pool; filter to the size band and region.
  4. Score each candidate 0–3 on four axes — industry match, size match, use-case fit, signal recency — and keep the top 5.
  5. For each kept company write a one-line why-it-fits tied to the won use case (not generic firmographics).
  6. Add the best-fit contact: name + role + LinkedIn/company URL. Email only if a verified source returns it. Otherwise mark not verified — enrich. Never guess or pattern-build emails.
  7. Write the markdown table, then the CSV (always) and offer XLSX via the xlsx skill. Save to the path the user names (default ./lookalikes/{use-case-slug}-targets.md + .csv).

Output -- exactly this shape

## Lookalike targets -- <use case> -- <YYYY-MM-DD>

**Seed:** <industry> · <size band> · <region> · use case: <one line>
**Sources:** timeln-find | web/Exa | Apollo/Clay (if used)

| # | Company | Why it fits (vs use case) | Industry | Size | Buying signal (date + source) | Contact (name · role) | Contact detail | Score /12 |
|---|---------|---------------------------|----------|------|-------------------------------|-----------------------|----------------|-----------|
| 1 | | | | | | | verified / not verified — enrich | |

**Scoring:** industry + size + use-case fit + signal recency, each 0–3.

**Excluded / parked**
- <company> — <reason>

**Next step:** `/cos-pursue {company} for {use case}` to draft outreach (cold-start).

CSV columns mirror the table (one row per company). Confidence = the /12 score.

Rules

  • Top 5 only — tight beats wide. Park extras under "Excluded / parked" with a reason.
  • Every company carries a source URL or a timeln-find title; no unsourced names.
  • Contact emails are verified-source-only. No domain-pattern guessing, ever.
  • why-it-fits must reference the won use case, not just "same industry".
  • Do not write outreach copy here — hand off to consult-pursue.
  • If a signal can't be found for a candidate, keep it but score signal-recency 0 and say no recent signal.

Common failure modes

MistakeFix
Generic "same vertical" rationaleTie why-it-fits to the buyer's reason for the won use case
Guessed emails (first.last@)not verified — enrich; only verified-source emails go in
20-company dumpScore, keep top 5, park the rest
Listing the won client or its direct competitorHonor exclusions; default-exclude the won client
Drifting into a pitchStop at the list; point to /cos-pursue

What ships with it: 1 file

919 B alongside SKILL.md

templates/

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.