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/o2alexanderfedin/strategic-research-automation-templateWrote 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/o2alexanderfedin/strategic-research-automation-template/score-opportunity)<a href="https://agentmods.dev/commands/o2alexanderfedin/strategic-research-automation-template/score-opportunity"><img src="https://agentmods.dev/badge/commands/o2alexanderfedin/strategic-research-automation-template/score-opportunity/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/o2alexanderfedin/strategic-research-automation-template/score-opportunity"><img src="https://agentmods.dev/badge/commands/o2alexanderfedin/strategic-research-automation-template/score-opportunity.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 | $0.00000 | $0.00331 |
| Opus 5.5 | $0.00000 | $0.00132 |
| Sonnet 5.5 | $0.00000 | $0.00066 |
| Haiku 4.5 | $0.00000 | $0.00033 |
Grade A, and why
score-opportunity 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 2mo 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
Score Opportunity
Objective
Apply scoring rubric to evaluate strategic opportunity.
Usage
/score-opportunity 01
Scoring Process
1. Load Scoring Rubric
- Read
config/scoring-rubric.yml - Understand categories, weights, and criteria
2. Extract Findings
- Review all research files from sprint
- Extract relevant data for each scoring criterion
3. Score Each Criterion (0-100)
Evaluate each criterion based on research:
- 90-100: Exceptional - Market-leading position, minimal risk
- 70-89: Strong - Clear advantage, manageable risks
- 50-69: Moderate - Viable but requires significant effort
- 30-49: Weak - Major challenges, questionable viability
- 0-29: Poor - Fundamental issues, not recommended
4. Calculate Category Scores
For each category:
Category Score = Σ (Criterion Weight × Criterion Score)
5. Calculate Final Score
Final Score = Σ (Category Weight × Category Score)
6. Determine Recommendation
Based on thresholds in rubric:
- ≥80: Strong Go - Highly recommended
- 65-79: Go - Recommended with confidence
- 50-64: Conditional Go - Proceed with caution
- <50: No Go - Not recommended
Output
- Detailed scoring breakdown by category and criterion
- Final score (0-100)
- Recommendation with justification
- Key risk factors and mitigation needs
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.
- 2mo ago First seen · 52 lines · 0 tokens per session scan A e0e4cdbbf424
score-opportunity is a command published in the GitHub repository o2alexanderfedin/strategic-research-automation-template (19 stars, last pushed 11mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 331 tokens. 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 commands, from other repositories
synthesize
Synthesize what the recent evaluations mean before dispatching more work. This step closes the gap between "config sweeper" and "research agent.".
audit-candidate
Walk the highest-signal suspicious candidate through an implementation audit.
consolidate
Write a compact checkpoint summary of the current frontier.
frame-break
Trigger a frame-break cycle only after cheap probes and audits are no longer productive.
why-stuck
Diagnose why the frontier is not moving.
tutor
Learn SDD conversationally - the agent becomes your tutor, by levels, with real validation as the grader / Aprende SDD conversando - el agente es tu tutor, por niveles, con validación real como corrector.