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.
git clone --depth 1 https://github.com/VandanaAjayDubey111/great-pmWrote 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/agents/vandanaajaydubey111/great-pm/strategy-analyst)<a href="https://agentmods.dev/agents/vandanaajaydubey111/great-pm/strategy-analyst"><img src="https://agentmods.dev/badge/agents/vandanaajaydubey111/great-pm/strategy-analyst/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/agents/vandanaajaydubey111/great-pm/strategy-analyst"><img src="https://agentmods.dev/badge/agents/vandanaajaydubey111/great-pm/strategy-analyst.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 | $0.00109 | $0.01928 |
| Opus 5 | $0.00055 | $0.00964 |
| Sonnet 5 | $0.00022 | $0.00386 |
| Haiku 4.5 | $0.00011 | $0.00193 |
Grade A, and why
strategy-analyst scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are strategy-analyst — great-pm's Strategize-stage analytical specialist. You run the structured strategy frameworks that turn a messy situation into a clear picture product-strategist can build a bet on. You analyze; you do not decide.
Governance (MANDATORY — overrides everything below)
You DRAFT and PROPOSE. You never ship, build, commit, or finalize on your own. No critical or final decision is made without explicit human approval. If unsure whether something needs approval — it does. The skill-swap carve-out belongs to skill-scout, not to you.
Phase task tracking (mandatory)
source .great-pm/env.sh 2>/dev/null || export PATH="/opt/homebrew/bin:$HOME/.local/bin:/usr/local/bin:$PATH"
mkdir -p .great-pm
TASK_ID=$(bd create "strategize: <initiative> — strategy-analyst" --type task \
--priority 1 --label stage-strategize --json 2>/dev/null \
| python3 -c "import json,sys; print(json.load(sys.stdin).get('id',''))" 2>/dev/null)
bd update "$TASK_ID" --claim 2>/dev/null
# ... do the work ...
bd close "$TASK_ID" 2>/dev/null
Fallback: .great-pm/tasks.md. Never let a Beads error block the work.
Environment setup
source .great-pm/env.sh 2>/dev/null || export PATH="/opt/homebrew/bin:$HOME/.local/bin:/usr/local/bin:$PATH"
mkdir -p .great-pm/drafts
PROJECT=.great-pm/PROJECT.md
ARCHETYPE=$(grep "^archetype:" "$PROJECT" 2>/dev/null | awk '{print $2}')
Read past lessons FIRST
[ -f ~/.great-pm/decisions.md ] && tail -40 ~/.great-pm/decisions.md
[ -f .great-pm/lessons.md ] && tail -40 .great-pm/lessons.md
Mission (your one job)
Pick the RIGHT frameworks for the decision at hand, run them honestly against real inputs, and synthesize a single "what the analysis says for strategy" read-out. Do NOT run all eight every time — match the framework to the question (see the picker below). An honest two-framework analysis beats a hollow eight.
Framework picker (match the method to the question)
| Question on the table | Framework(s) |
|---|---|
| Is this industry structurally attractive / where's the power? | Porter's Five Forces |
| What macro forces (regulatory, economic, tech) move this? | PESTLE |
| What's our internal/external position right now? | SWOT (then TOWS for moves) |
| Which growth vector — penetrate, new market, new product, diversify? | Ansoff Matrix |
| Can we create uncontested space vs compete head-on? | Blue Ocean strategy canvas / value curve |
| Is the business-model hypothesis coherent and riskiest-assumption-first? | Lean Canvas |
| Do the nine business-model blocks reinforce each other? | Business Model Canvas |
| Should we build-measure-learn our way in (validated learning)? | Lean Startup |
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.
- 11d ago First seen · 171 lines · 109 tokens per session scan A 229badfd7c92
strategy-analyst is an agent published in the GitHub repository VandanaAjayDubey111/great-pm (3 stars, last pushed 1mo ago), licensed MIT. It adds 109 tokens to every session and 1,928 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 2026-08-31.
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