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 OneWave-AI/claude-skills --skill competitor-intel-agentgit clone --depth 1 https://github.com/OneWave-AI/claude-skillsWrote 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/onewave-ai/claude-skills/competitor-intel-agent)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/competitor-intel-agent"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/competitor-intel-agent/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/onewave-ai/claude-skills/competitor-intel-agent"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/competitor-intel-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00039 | $0.00598 |
| Opus 5 | $0.00019 | $0.00299 |
| Sonnet 5 | $0.00008 | $0.00120 |
| Haiku 4.5 | $0.00004 | $0.00060 |
Grade A, and why
competitor-intel-agent 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 — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitor Intelligence Agent
Track competitor activity across multiple dimensions, detect meaningful changes, interpret the signals, and deliver actionable intelligence that builds historical context over time. Act as an analyst that connects dots, not a raw scraper.
Contents
references/directory-structure.md-- tracking directory layout,config.yaml, andusage-history.jsontemplatesreferences/monitoring-dimensions.md-- the six monitoring dimensions with per-dimension analysis frameworks, detection protocols, and snapshot output formatsreferences/intel-report-format.md-- the full intelligence report templatereferences/scoring-and-rules.md-- change-detection scoring, trend protocol, data-quality rules, execution rules, quick commands
Workflow
- Determine the operating mode on invocation:
- Setup (no tracking directory exists): collect the user's company name and description, competitor URLs/domains, priority monitoring dimensions, and output directory (default
./competitor-intel/). Create the directory structure andconfig.yaml. Seereferences/directory-structure.md. - Monitoring run (tracking directory exists): proceed to steps 2-7.
- Report only (user wants a report without new monitoring): read existing snapshots and change logs, synthesize trends, and generate strategic recommendations using
references/intel-report-format.md.
- Setup (no tracking directory exists): collect the user's company name and description, competitor URLs/domains, priority monitoring dimensions, and output directory (default
- Read
config.yamlto load the competitor list and settings, then read the most recent snapshot for each competitor and dimension. - Execute monitoring across all configured dimensions. Apply the detection protocol for each dimension in
references/monitoring-dimensions.md. - Compare new data against previous snapshots. Score every change for magnitude per
references/scoring-and-rules.md; flag changes rated 4-5 as immediate alerts. - Write dated snapshots in the per-dimension output formats and log detected changes under the competitor's
changes/folder. - Generate the intelligence report following
references/intel-report-format.md. When 3 or more snapshots exist for a competitor, add longitudinal trend analysis. - Update
usage-history.jsonwith the run metadata.
What ships with it
4 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.
- 12d ago First seen · 40 lines · 39 tokens per session scan A 5f749c2d0ffe
competitor-intel-agent is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 598 once invoked, about $0.0002 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.
Other skills, from other repositories
analytics-strategy
Design measurement frameworks including event taxonomy, KPI hierarchy, dashboard architecture, attribution models, and analytics implementation strategy. Use this skill whenever the user wants to plan analytics, design dashboards, build event taxonomies, define KPIs, set up tracking, or audit existing measurement.…
content-strategy
Develop a content strategy covering editorial positioning, content pillars, formats, calendar, governance, and topical authority planning. Use this skill whenever the user wants to plan a content program, define content pillars, build an editorial calendar, structure topic clusters, set up content governance, or align…
incident-response
Manage active production incidents through detection, triage, mitigation, communication, and resolution with structured roles and decision-making. Use this skill whenever the user has an active incident, a production issue, a service outage, a security incident, or needs to plan incident response procedures. Triggers…
stakeholder-communication
Communicate effectively with stakeholders across functions and seniority levels. Use this skill when writing status updates, preparing executive reviews, sharing technical decisions with non-technical audiences, managing up, communicating bad news, or designing the communication cadence for a project. Triggers on…
review-work
Post-implementation gate review: run manual QA on the real surface yourself, then launch ONE gate reviewer (never a panel) to audit goal, constraints, code quality, security, missed context, and QA evidence. Use before a PR handoff or when the user explicitly asks to review completed work.
agb-begriff-vorformuliert-305
Für AGB Begriff Vorformuliert 305: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: agb-begriff-vorformuliert-305.