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 MoizIbnYousaf/marketing-cli --skill company-researchgit clone --depth 1 https://github.com/MoizIbnYousaf/marketing-cliWrote 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/moizibnyousaf/marketing-cli/company-research)<a href="https://agentmods.dev/skills/moizibnyousaf/marketing-cli/company-research"><img src="https://agentmods.dev/badge/skills/moizibnyousaf/marketing-cli/company-research/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/moizibnyousaf/marketing-cli/company-research"><img src="https://agentmods.dev/badge/skills/moizibnyousaf/marketing-cli/company-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 39 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00102 | $0.02144 |
| Opus 5 | $0.00051 | $0.01072 |
| Sonnet 5 | $0.00020 | $0.00429 |
| Haiku 4.5 | $0.00010 | $0.00214 |
Grade A, and why
company-research 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 12d 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
On Activation
- Read
brand/positioning.md,brand/competitors.md, andbrand/audience.mdif present. Ground queries in the brand's category and known competitors. All optional. - Confirm Exa MCP Agent tools or
EXA_API_KEY. If missing, stop with the install hint from Prerequisites /mktg doctor. - Default to Exa Agent for deep dives and lists; use advanced search only for quick single lookups.
- When
/cmoor a research agent owns the brand write, return structured findings + sources - do not silently overwritebrand/competitors.mdunless the user asked to update brand memory.
Company Research
mktg runtime note
Prefer Exa MCP when available (tools: web_search_exa, web_search_advanced_exa, web_fetch_exa, agent_run).
If MCP Agent tools use the older create/wait/get names (agent_create_run, agent_wait_for_run, agent_get_run_output), use those equivalently.
Without MCP, call the HTTP API with x-api-key: $EXA_API_KEY (POST https://api.exa.ai/search, /contents, /agent).
Firecrawl remains the path for deep scrape of a known URL after Exa discovery.
Tool Selection (Critical)
Two Exa surfaces, two jobs:
- Exa Agent (
agent_run, or legacyagent_create_run/agent_wait_for_run/agent_get_run_output) - the default for company research. Use it for deep dives, competitor analysis, multi-angle research (product + funding + news + people), and building company lists. One Agent run handles query decomposition, multi-step searching, and synthesis internally - do not orchestrate many manual searches for work an Agent run covers. web_search_advanced_exa- quick, low-latency lookups: a fastcategory: "company"discovery pass, a single news check, or finding a homepage.
Do NOT use other Exa tools.
Deep Dives and Lists: Exa Agent
Agent runs are async: create the run, wait for it, then read the output.
agent_create_runwith a natural-languagequeryand, when you want repeatable structure, anoutputSchema(bound arrays withmaxItems). Returns anagent_run_...ID.agent_wait_for_rununtil the run iscompleted(call again if still running).agent_get_run_output- readoutput.textoroutput.structured, plusoutput.groundingcitations.
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.
- 12d ago First seen · 199 lines · 102 tokens per session scan A 03dafb9fe55c
company-research is a skill published in the GitHub repository MoizIbnYousaf/marketing-cli (31 stars, last pushed today), licensed MIT. It adds 102 tokens to every session and 2,144 once invoked, about $0.0005 per session on Opus 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 2026-08-30.
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