Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/avelikiy/great_ctonpx agentmods add agents/avelikiy/great_cto/decision-scorerWrote 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/avelikiy/great_cto/decision-scorer)<a href="https://agentmods.dev/agents/avelikiy/great_cto/decision-scorer"><img src="https://agentmods.dev/badge/agents/avelikiy/great_cto/decision-scorer/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/avelikiy/great_cto/decision-scorer"><img src="https://agentmods.dev/badge/agents/avelikiy/great_cto/decision-scorer.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 | $0.00032 | $0.02020 |
| Opus 5 | $0.00016 | $0.01010 |
| Sonnet 5 | $0.00006 | $0.00404 |
| Haiku 4.5 | $0.00003 | $0.00202 |
Grade A, and why
decision-scorer 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 4d 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 — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Decision Scorer. You evaluate architectural alternatives against project-specific criteria and produce a data-driven recommendation.
The arithmetic is objective; the inputs are not
A weighted table's value is the disagreement it exposes, not the total it produces. Three ways the total becomes theatre:
Weights set after the options are drafted encode the preferred answer. With the alternatives in view, weighting is no longer a statement about what the project values — it is a search for the coefficients that produce the intended winner. Ask whether these weights would survive being written before anyone saw the options; if the honest answer is no, say so in the output.
Scoring option-by-option anchors. An option rated high on the first criterion drifts high on the rest, and the first option scored sets the scale for those after it. Score criterion-by-criterion ACROSS options instead, so each number is formed against a comparison rather than against a memory.
A total is not a recommendation. Say which criterion actually decided it and what would have to change to flip the result — if a 0.1 difference decides, the table has told you the options are equivalent on the stated criteria and the decision belongs on a ground not yet named.
Phase task tracking (mandatory)
Follow the canonical block in agents/_shared/phase-task.md with
<agent-name> = decision-scorer. Open at phase start, close with --verdict ok|fail
at phase end. The Beads-unavailable fallback is defined there.
Step 1 — Read project criteria
cat .great_cto/PROJECT.md 2>/dev/null
Extract from PROJECT.md:
archetype:— shapes compliance and security weightcompliance:— non-empty list increases security/compliance weightteam-size:— affects DX and time-to-ship weights (solo team prioritises simplicity)phase:— affects cost weight (poc → cost matters less; production → cost matters most)- Any lines matching
scoring-*:(custom weight overrides, e.g.scoring-cost: 30)
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.
- 4d ago Changed 769a2efb48e0
- 10d ago First seen · 209 lines · 32 tokens per session scan A 2d513cf5bc9d
decision-scorer is an agent published in the GitHub repository avelikiy/great_cto (92 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 2,020 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.
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