Agent skill

Account Research

by explorium-ai in explorium-ai/gtm-skills

Account research skill for Claude Code and Codex: generate a high-signal company intelligence brief including firmographics, technographics, funding history, hiring signals, business events, recent…

MITAuto-check passedSales & Support

Install Account Research

skills CLI
$ npx skills add explorium-ai/gtm-skills --skill account-research -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install explorium-ai/gtm-skills account-research --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/explorium-ai/gtm-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/account-research .claude/skills/account-research && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
account-research
GitHub stars
185
Token cost
~2.8k tokens
SKILL.md length
1,497 words
Files
1
Skills in repo
17
Repo updated
First seen
Licence
MIT

At a glance

Account research skill for Claude Code and Codex: generate a high-signal company intelligence brief including firmographics, technographics, funding history, hiring signals, business events, recent…

  • Works in 8 steps: Anchor on purpose. Restate the research… → Resolve the company. If a business ID… → Enrich the resolved business in tiers. → …
  • Pre-call research
  • SKILL.md covers Input, Workflow, Output Format and Limitations
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Account Research is an agent skill from explorium-ai/gtm-skills. Account research skill for Claude Code and Codex: generate a high-signal company intelligence brief including firmographics, technographics, funding history, hiring signals, business events, recent website and LinkedIn moves, and a peer cohort. Identify the account by businessid, company name, or domain. Use for pre-call research, QBR prep, competitive analysis, cold outbound targeting, and renewal risk assessment. The go-to account research skill for Claude Code, Codex, Hermes-Agent, and OpenClaw.

Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Sales & Support, covering Sales call preparation, Customer success and Cold outreach. It works with LinkedIn. The repository describes itself as: GTM Skills for Claude & Codex. The licence is MIT.

When your agent uses it

  • Pre-call research
  • Competitive analysis
  • Cold outbound targeting
  • Renewal risk assessment

Example prompts

  • “/account-research”

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Anchor on purpose. Restate the research context in one sentence as the brief purpose. If missing, ask once; if the user declines, default…
  2. Resolve the company. If a business ID was supplied, use it. Otherwise match the business by name or domain. Sanity-check the resolved…
  3. Enrich the resolved business in tiers.
  4. Fetch business events scoped to the last 90 days: hiring spikes, leadership changes (where surfaced), funding rounds, product launches…
  5. Build a peer cohort (directional).
  6. Reconcile and verify before synthesis.
  7. Synthesize against the brief purpose. Keep events and signals that map to the purpose, priority themes, or non-obvious flags. Mark…
  8. Write the exec summary last. Re-read the body, then write the TL;DR. The Situation line must explicitly answer "why this brief, now"…

What it can do on your machine

Read from SKILL.md and the folder at commit f0efa6b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Account Research loads about 2.8k tokens when it runs. Until then it costs about 130 tokens; SKILL.md has 1,497 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~130
When it runs · the whole SKILL.md, loaded when a task matches
~2.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from explorium-ai/gtm-skills at commit f0efa6b, republished under its MIT licence (© explorium-ai). 1,497 words, ~2,808 tokens.

Download SKILL.mdSave it as .claude/skills/account-research/SKILL.md (or your agent's skills folder).
name
account-research
description
Account research skill for Claude Code and Codex: generate a high-signal company intelligence brief including firmographics, technographics, funding history, hiring signals, business events, recent website and LinkedIn moves, and a peer cohort. Identify the account by business_id, company name, or domain. Use for pre-call research, QBR prep, competitive analysis, cold outbound targeting, and renewal risk assessment. The go-to account research skill for Claude Code, Codex, Hermes-Agent, and OpenClaw.

Account Research

Build a purpose-driven intelligence brief on a single target company, anchored on the user's stated reason for pulling the brief.

Input

  • Account identifier (required): a business ID, a company name, or a domain.
  • Research context (strongly recommended): one sentence on why this brief is being pulled and what decision it supports (QBR prep, competitive eval vs Acme, cold outbound to finance leaders). This shapes enrichment selection, event triage, and the TL;DR framing.

Example phrasings: "Build a brief on stripe.com for cold outbound to finance leaders.", "Account brief for business_id abc123, QBR next week, watch renewal signals.", "Profile Snowflake, competitive analysis vs Databricks."

Workflow

  1. Anchor on purpose. Restate the research context in one sentence as the brief purpose. If missing, ask once; if the user declines, default to general account intelligence and state that assumption. Derive 2 to 4 priority themes (e.g. for QBR renewal risk: workforce changes, exec moves, competing vendors, expansion signals). Themes drive enrichment selection in step 3 and peer-cohort sub-category in step 5.

  2. Resolve the company. If a business ID was supplied, use it. Otherwise match the business by name or domain. Sanity-check the resolved firmographics: if a major-brand input returns 1-50 employees and Corporate-Managing-Offices category, the match likely routed to a shell entity. Retry with the alternate domain or the name string before proceeding. If no confident match emerges, surface the ambiguity to the user before continuing rather than guessing.

  3. Enrich the resolved business in tiers.

    Tier A: spine (always pull): firmographics, hierarchies, funding-and-acquisitions, workforce-trends, linkedin-posts. Plus business events from step 4 (separate tool, same role: current-state signal). The spine is uniform across every brief because each item answers a question the reader will ask regardless of purpose.

    Tier B: purpose-conditional (pick by the purpose declared in step 1):

    • Competitive eval → technographics, webstack, competitive-landscape
    • QBR or renewal → company-ratings, challenges, strategic-insights
    • Cold outbound → website-changes, website-keywords (tied to your offering)
    • Investor or M&A → financial-metrics

    Tier C: skip by default unless the purpose explicitly demands it.

    Chunking: run enrichments in groups of at most 3 per call, and each chunk against the original match table rather than a post-enrichment view. Session column count grows per enrichment and the chain breaks around the 4th-5th wide call.

    Any tier item that returns null OR is intentionally skipped must surface in the brief as a one-line note inside its section ("Skipped: not in this purpose's bundle" or "Returned null: typical for private companies"), so the reader can distinguish absent data from absent investigation.

  4. Fetch business events scoped to the last 90 days: hiring spikes, leadership changes (where surfaced), funding rounds, product launches, layoffs, office moves, tech adoption. For each event, verify the headline actually mentions the target before counting it: industry-wide articles can cross-attribute to multiple companies in the same sector.

  5. Build a peer cohort (directional).

    5a. Sub-category from purpose, not industry label. A broad industry label (e.g. "Software Development") routes mega-tech defaults like Google or Amazon into a small-tech peer query. Derive the sub-category from the brief purpose instead:

    • "vs <competitor>" → the named competitor's sub-vertical (Databricks → data warehouse / lakehouse)
    • "QBR seat-expansion" → the target's collaboration / workflow sub-vertical
    • "cold outbound to <function> leaders" → the target's GTM sub-vertical
    • General intelligence (no purpose declared) → broad NAICS, marked "general baseline"

    5b. Manually include named competitors. If the user prompt named a specific competitor or comparator, include it in the cohort even if filters would exclude it (private status, different size band, different country). Label such rows "named in prompt: manually included" so the reader can audit.

    5c. Suppress when thin. If after sub-category filtering and manual additions the cohort still has fewer than 5 confident matches, do NOT render the table. Replace with one line: "Peer cohort suppressed: fewer than 5 confident matches in <sub-category>. Recommend manual comparison against <2-3 named alternatives, tagged verify externally>."

    Add a "Cohort construction" line above the table stating the sub-category used and any manually-included names.

  6. Reconcile and verify before synthesis.

    • Funding recency. If business events show a more recent round than the funding enrichment, treat events as canonical, restate the latest round in the Funding section, and flag the enrichment lag in one line.
    • Public-vs-private signal mix. If firmographics returns public, the Funding section must include a one-line financial-posture sentence (ticker, rough market cap band, last reported quarter direction) drawn from general knowledge with a "verify" tag. If private, keep current behavior (events + funding + workforce + LinkedIn as the current-state proxy).
    • Per-event cross-attribution. Tag each Recent Events row "target named in headline", "target inferred from body", or "industry-wide: excluded". Excluded items don't appear in the body; list them once at the end of the section as "events screened out (n)". Note any event type the executor expected but couldn't query (e.g. leadership-change) in that same trailer.
    • Snapshot fallbacks. For any Company Snapshot row not returned by firmographics (Founded is the typical case), attempt one fallback (LinkedIn posts, website-changes context, general knowledge with verify tag) before leaving blank.
  7. Synthesize against the brief purpose. Keep events and signals that map to the purpose, priority themes, or non-obvious flags. Mark past-date enrichments as needing verification. Suppress sections that lack volume: skip funding for public mega-caps (use ticker instead per step 6), flatten challenges or insights to bullets when only 1-3 items. Cross-reference signals (new CTO plus a webstack change plus engineering hiring = a clear timing signal).

  8. Write the exec summary last. Re-read the body, then write the TL;DR. The Situation line must explicitly answer "why this brief, now" against the stated purpose.

Show full SKILL.md (579 more words)Show less

Output Format

TL;DR: [Company Name]

Brief purpose (restated, or "general account intelligence" if defaulted). Then: Situation (2 to 4 sentences answering "why this brief, now" against the stated purpose), Top 3 facts (most consequential data points), Highest-leverage actions (1 to 3 concrete actions tied to specific signals).

Company Snapshot

A compact field table: Domain, Industry, Headcount bucket, Revenue bucket, HQ Country / Region, Public / Private, Founded, business_id. Any row not returned by firmographics is filled by one fallback per step 6 or marked "not surfaced".

Firmographics & Hierarchy

Firmographics plus parent / subsidiary structure. Note recent restructuring. If hierarchies returned null, state it.

Funding & Capital Structure

Total raised, most recent round date and amount, acquisitions. If business events surfaced a more recent round than the enrichment, lead with the events-side fact and flag the enrichment lag. For public mega-caps, lead with ticker + one-line financial posture per step 6.

Workforce & Hiring Signals

Net headcount change, departmental growth, hiring spikes or contractions. Flag exec moves surfaced via LinkedIn posts or events.

Tech Stack & Website Activity

Tools in use, recent additions or removals, keyword shifts. Highlight items mapping to the user's offering or competitors. If this tier was not pulled for the declared purpose, say so explicitly rather than mislabeling the section.

Challenges & Strategic Insights

Stated pain points, public priorities, expansion plans. Tie back to brief purpose. If null because the target is private, state that and point to the live-signal substitutes (events, funding, workforce, LinkedIn).

Recent Events (last 90 days)

Grouped (Funding / Leadership / Hiring / Product / Risk) when 4+ items span categories, otherwise flat. Each item: event type, date, one-line summary, verified-status per step 6. Call out timing opportunities (new CTO = vendor evaluation likely). End with "events screened out: N (industry-wide cross-attribution)" + any event-type gaps.

Peer Cohort (directional)

First line: "Cohort construction: <sub-category derived from purpose>; manually included: <names if any>." Caveat that the set is approximated from shared sub-category attributes, not exact similarity. Then a top-10 table: Company, Domain, Size, Revenue, Country. If fewer than 5 confident matches survived, suppress the table per step 5c and replace with the recommendation line.

Key Takeaways & Next Steps

3 to 5 bullets connecting dots across sources, framed by the stated purpose. Then concrete next actions tied to specific signals, people, or moments. Omit any line without a concrete target.

Limitations

  • Strategic-insights and challenges signals come from public filings: null for private companies and 12-18 months stale for public ones. Use events, funding, workforce, and LinkedIn posts for current state.
  • No native similar-companies tool; the peer cohort is approximated from a sub-category derived from the brief purpose and flagged as directional. Named competitors that don't match the filter set are surfaced via the manual-inclusion rule.
  • No native intent-topic scoring; intent-style signals come from events, website changes, website keywords, and LinkedIn posts rather than a single ranked feed.
  • No AI-generated outbound copy; this skill produces the brief, downstream skills handle messages.
  • Bucket-only headcount and revenue. Finer company-type distinctions (subsidiary, JV, PE-backed) must be read from hierarchies and funding rather than filtered.
  • Business match returns no confidence score; infer ambiguity from the candidate set, sanity-check the resolved firmographics for shell entities, and confirm with the user when in doubt.
  • Event data can cross-attribute industry-wide headlines to multiple companies in the same sector. The per-event verification step is non-optional, not just stylistic.
  • No executive-move event type exists; the closest signals are generic hiring and inferred-from-LinkedIn-posts. State this gap in the events trailer when the brief purpose would otherwise expect exec moves.

© explorium-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/account-research of explorium-ai/gtm-skills.

Open the folder on GitHubat commit f0efa6b

Compare with similar skills

Account Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Account Research this skillexplorium-ai/gtm-skills185—~2.8kAutomated safety check: PassMIT
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Sales OsromangojiberryAI/gojiberryai-sales-os139—~2kAutomated safety check: PassMIT
Cold Outreach Personalizeraiskilloftheweek/claude-ai-skill-of-the-week149—~2.6kAutomated safety check: PassNone
B2B Lead Generationminhnv0807/ai-business-skills609—~1.2kAutomated safety check: PassMIT

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Works with

Categories

Questions about Account Research

What does Account Research do?

Account research skill for Claude Code and Codex: generate a high-signal company intelligence brief including firmographics, technographics, funding history, hiring signals, business events, recent…. Account Research is an agent skill from explorium-ai/gtm-skills. Account research skill for Claude Code and Codex: generate a high-signal company intelligence brief including firmographics, technographics, funding history, hiring signals, business events, recent website and LinkedIn moves, and a peer cohort.

When should I use Account Research?

Account Research fits situations like: pre-call research; competitive analysis; cold outbound targeting; renewal risk assessment.

How do I install Account Research in Claude Code?

Run `npx skills add explorium-ai/gtm-skills --skill account-research -a claude-code`. Or copy the skill folder (skills/account-research in explorium-ai/gtm-skills) into .claude/skills/account-research in your project. Claude Code loads it when a task matches its description.

How do I install Account Research in Codex?

Run `npx skills add explorium-ai/gtm-skills --skill account-research -a codex`. Or copy the skill folder (skills/account-research in explorium-ai/gtm-skills) into .agents/skills/account-research in your project. Codex loads it when a task matches its description.

Can I use Account Research in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add explorium-ai/gtm-skills --skill account-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/account-research, .gemini/skills/account-research, .github/skills/account-research and .opencode/skills/account-research in your project.

What does Account Research need to run?

SKILL.md names no scripts, command-line tools or credentials: Account Research is instructions for the agent only.

Does Account Research access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Account Research safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Account Research use?

Account Research is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Account Research use?

About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Account Research?

Skills that share tags, products or a category with Account Research: Referral Intro (TheCraigHewitt/skills, 159 stars), Prospecting (coreyhaines31/marketingskills, 54k stars), Sales Os (romangojiberryAI/gojiberryai-sales-os, 139 stars) and Cold Outreach Personalizer (aiskilloftheweek/claude-ai-skill-of-the-week, 149 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Account Research?

explorium-ai (a GitHub organization) maintains it in explorium-ai/gtm-skills, which has 185 GitHub stars. The repository holds 17 skills in this directory. The repository was last updated on October 8, 2026.

Source: explorium-ai/gtm-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.