Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Aznatkoiny/zAI-Skills/plugin install consulting-toolkitWrote 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/commands/aznatkoiny/zai-skills/competitive-landscape)<a href="https://agentmods.dev/commands/aznatkoiny/zai-skills/competitive-landscape"><img src="https://agentmods.dev/badge/commands/aznatkoiny/zai-skills/competitive-landscape/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/commands/aznatkoiny/zai-skills/competitive-landscape"><img src="https://agentmods.dev/badge/commands/aznatkoiny/zai-skills/competitive-landscape.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 | $0.00009 | $0.00671 |
| Opus 5 | $0.00005 | $0.00336 |
| Sonnet 5 | $0.00002 | $0.00134 |
| Haiku 4.5 | $0.00001 | $0.00067 |
Grade A, and why
competitive-landscape 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 8d 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.
What it actually says
You are a senior consultant at a top-tier strategy firm. Produce a competitive landscape analysis rigorous enough for a partner to present to a client CEO. Every claim must be sourced. The output should surface strategic implications, not just describe competitors.
Build a competitive landscape analysis for: $ARGUMENTS
Data sourcing: for US public competitors, first pull revenue and margin data with mcp__financial-intelligence__fin_get_company_financials and side-by-side comparisons with mcp__financial-intelligence__fin_compare_companies; cite as [SEC EDGAR, date]. Use WebSearch only for private players, market share estimates, and recent strategic moves. If the MCP tools are unavailable, fall back to WebSearch and state so.
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COMPETITOR PROFILES (top 5-7 players) — for each:
- Revenue and/or market share (sourced, with year)
- Core value proposition and key differentiators
- Strategic focus and recent moves (M&A, product launches, geographic expansion)
- Strengths and vulnerabilities
- Trajectory: gaining, holding, or losing position — and why
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COMPETITIVE POSITIONING MAP — define two strategic axes that capture the most meaningful differentiation in this market (e.g., price vs. breadth, innovation vs. scale). Place each competitor. Explain why you chose these axes — they should reveal strategic trade-offs, not just describe obvious dimensions.
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STRUCTURAL ANALYSIS — apply Porter's Five Forces or an equivalent framework:
- What drives rivalry intensity?
- Where does power sit (buyers, suppliers, platforms)?
- What are the barriers to entry and substitution threats?
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STRATEGIC IMPLICATIONS — this is the "so what":
- Where is the white space?
- Which competitive positions are defensible vs. vulnerable?
- What are the implications for the client's strategy?
- What would you watch for over the next 12-24 months?
<quality_standards>
- Source all revenue/share figures: [Source, Date].
- Clearly distinguish between confirmed data and your inferences.
- Do not just describe competitors — extract the insight. Every section needs a "so what."
- The positioning map must have clearly defined, non-obvious axes with a rationale. </quality_standards>
<output_format>
Start from the skeleton at ${CLAUDE_PLUGIN_ROOT}/templates/competitive-landscape.md — it prewires the 2x2 positioning map and the capability table.
- Executive summary (3-5 bullets)
- Competitive arena definition
- Competitor comparison table (name | revenue | share | differentiator | trajectory)
- Individual competitor profiles (1 paragraph each)
- Positioning map (described with axes and placements)
- Structural analysis
- Strategic implications and white space
- Sources </output_format>
Save output as competitive-landscape-[topic].md in the working directory.
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.
- 8d ago First seen · 56 lines · 9 tokens per session scan A b51165f44302
competitive-landscape is a command published in the GitHub repository Aznatkoiny/zAI-Skills (9 stars, last pushed 1mo ago), licensed MIT. It adds 9 tokens to every session and 671 once invoked, about $0.0000 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 2026-08-31.
Other commands, from other repositories
strip
This is the task-based stripper, not the always-on prior: a deliberate cleanup pass you asked for. Apply the fp-minify doctrine to the target and remove or compress comments that don't earn their place.
conjure-config
Set, view, or remove conjure preferences. Asks questions to understand what you want, then writes plain-language instructions that conjure commands follow automatically.
setup
A command that creates a Korean-language CLAUDE.md project guide from a template. CLAUDE.md is a file containing instructions and project context for the Claude coding assistant.
dock-chat
Dock the full conversation to Telegram — drive Claude from your phone.
undock
Undock from Telegram — resume normal terminal replies and approvals.
dock-approvals
Route Claude Code permission prompts to Telegram — step away briefly.