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 agentmods add skills/viktorbezdek/skillstack/competitive-intelligencenpx skills add viktorbezdek/skillstack --skill competitive-intelligencegit clone --depth 1 https://github.com/viktorbezdek/skillstackWhat 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 | $0.00153 | $0.00517 |
| Opus 5 | $0.00077 | $0.00259 |
| Sonnet 5 | $0.00031 | $0.00103 |
| Haiku 4.5 | $0.00015 | $0.00052 |
Grade A, and why
competitive-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 2d 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
competitive-intelligence
Competitor analysis, market sizing, positioning maps, win/loss pattern synthesis, and battlecard creation for product and GTM decisions.
When to use
- Map the competitive landscape for AI code assistants (GitHub Copilot, Cursor, etc.)
- Create a battlecard for our sales team competing against Datadog
- Analyse our last 50 win/loss notes — what patterns do you see?
- How should we position against a competitor that's 10x larger?
- Estimate the TAM for developer productivity tools in enterprise
- What are the defensible moats in the observability market?
- Identify the positioning gaps in the MLOps tool landscape
- Compare our feature set against three competitors in a matrix
When NOT to use
- Run customer interviews to validate our positioning hypothesis — Primary research — not CI synthesis
- Build a three-year financial model for our go-to-market plan — Financial modelling — out of scope
- Design our pricing tiers and annual contract structure — Pricing strategy — separate concern
- Write a press release about our product launch — Comms/PR — not competitive intelligence
Anti-patterns
Symptom
Invoking this skill for tasks outside its scope — e.g., infrastructure concerns when the request is about application code, or vice versa.
Problem
Scope mismatch wastes context and produces advice tuned for the wrong domain. A database schema skill answering a connection-pooling question gives schema advice when the real problem is operational configuration.
Solution
Read the NOT for clauses carefully. If the request matches an exclusion, identify the correct skill (check SkillStack for the right domain) rather than stretching this skill to cover adjacent ground.
What ships with it
2 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.
- 2d ago First seen · 40 lines · 153 tokens per session scan A b9e264968252
competitive-intelligence is a skill published in the GitHub repository viktorbezdek/skillstack (11 stars, last pushed 2mo ago), licensed MIT. It adds 153 tokens to every session and 517 once invoked, about $0.0008 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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