Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add alebgl77/claude-inc --skill account-intelligencegit clone --depth 1 https://github.com/alebgl77/claude-incWrote 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/alebgl77/claude-inc/account-intelligence)<a href="https://agentmods.dev/skills/alebgl77/claude-inc/account-intelligence"><img src="https://agentmods.dev/badge/skills/alebgl77/claude-inc/account-intelligence/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/alebgl77/claude-inc/account-intelligence"><img src="https://agentmods.dev/badge/skills/alebgl77/claude-inc/account-intelligence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00088 | $0.01475 |
| Opus 5.5 | $0.00035 | $0.00590 |
| Sonnet 5.5 | $0.00018 | $0.00295 |
| Haiku 4.5 | $0.00009 | $0.00147 |
Grade A, and why
account-intelligence scanned grade A with 0 findings 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 1mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Account Intelligence — Signal Analyst
When to use
Build an account cohort, validate a growth trigger, support ABM or investigate product-led sales readiness. For a single active deal's call preparation and personal outreach, hand the accepted account to Sales and its account-research manual.
Inputs
- ICP version, must-haves, exclusions, target business problem and qualification decision.
- Approved account sources or user-provided exports; existing account IDs and exclusions from Sales.
- Research horizon, maximum cohort size, data minimization requirements and freshness windows.
- Public page snapshots or authorized first-party account events; access scope and source metadata.
Workflow
- Define the unit. Choose the legal/operating account and stable ID. Record parent/subsidiary relationships and deduplicate aliases/domains before scoring. Exclude existing opportunities, competitors or customers when the experiment requires it.
- Specify signals before research. Name observable facts relevant to the problem: a dated workflow launch, an integration requirement, a published operations role or authorized repeated product use. Define where to look and what would disconfirm relevance. Funding and hiring alone do not establish budget, pain or buying intent.
- Collect minimally. Prefer first-party company pages and authorized exports. Save source URL, publisher, precise supporting excerpt or selected value, snapshot hash where available, and researcher. Do not collect contact lists, sensitive attributes or hidden identifiers. Follow source access limits; do not bypass access controls.
- Separate clocks.
event_atis the event's asserted date;published_atis the page's claimed publication date;observed_atis when a researcher actually saw or captured it;extracted_atis when a parser processed a saved file. Unknown stays null. A current extraction does not refresh an old observation. Record the timezone and whether each date is source-asserted or independently recorded. - Validate and decay. Label direct evidence, corroborated inference or unverified claim. Set
valid_untiland a concrete recheck per signal type. Starting policy: job/change signals recheck within 30 days; firmographic fit within 90 days; product usage within the agreed recent account window. These are operating defaults, not statistical truths. Expired or undated signals can inform research but cannot satisfy a freshness gate. - Qualify explainably. Publish a rubric before ranking. Score evidence-backed fit separately from readiness; require must-haves and no exclusions. Missing evidence is unknown, never a silent zero or an inferred positive. Show rule-by-rule evidence and reason codes. A score is a prioritization rule, not a conversion probability.
- Test relevance. Inspect a sample of both high and low scores, including stale and contradictory records. Review likely false positives with Sales. Compare later acceptance by score band and revise the rubric only on a new version/cohort.
- Hand off and reconcile. Give Marketing an audience/problem brief with proof and Sales an account packet with open questions, freshness and proposed next step. Sales decides outreach and commercial qualification. Record accepted/rejected/deferred reasons and send outcomes to
revenue-operations; do not create or update CRM deals without authorized Sales ownership.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 73 lines · 88 tokens per session scan A 5a10e191c65a
account-intelligence is a skill published in the GitHub repository alebgl77/claude-inc (22 stars, last pushed 15d ago), licensed MIT. It adds 88 tokens to every session and 1,475 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-27.
account-intelligence compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| account-intelligencealebgl77/claude-inc | Skill | 22 | 15d ago | MIT | A | 88 | Claude Code |
| mcp-larkaahl/skills | Skill | 164 | 1mo ago | MIT | A | 45 | Claude Code, Codex |
| checklistdeciqAI/knowledge-skills | Skill | 13 | 12d ago | MIT | A | 105 | Claude Code, Codex |
| deep-workdeciqAI/knowledge-skills | Skill | 13 | 12d ago | MIT | A | 123 | Claude Code, Codex |
| dichotomy-of-controldeciqAI/knowledge-skills | Skill | 13 | 12d ago | MIT | A | 143 | Claude Code, Codex |
| intrinsic-drivedeciqAI/knowledge-skills | Skill | 13 | 12d ago | MIT | A | 107 | Claude Code, Codex |
| knowing-and-doing-as-onedeciqAI/knowledge-skills | Skill | 13 | 12d ago | MIT | A | 118 | Claude Code, Codex |