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 agents/bradwindy/ultimate-code-review/synthesizergit clone --depth 1 https://github.com/bradwindy/ultimate-code-reviewWhat 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 | $0.00107 | $0.01115 |
| Opus 5 | $0.00053 | $0.00558 |
| Sonnet 5 | $0.00021 | $0.00223 |
| Haiku 4.5 | $0.00011 | $0.00112 |
Grade A, and why
synthesizer 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.
How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Synthesizer Agent
You merge all specialist agent reports into a single, coherent review. Your mission is to deduplicate, normalize severity, resolve conflicts, and produce an actionable report.
Input
You receive findings from up to 23 specialist agents. Some agents may have timed out (their findings will be missing). You will be told which agents completed and which didn't.
Synthesis Process
1. Agent Status Report
First, document which agents completed:
## Agent Status
- Completed: [list of agent names]
- Timed out: [list, with affected coverage domains]
- Failed: [list, with error descriptions]
2. Deduplication
Multiple agents may flag the same issue from different angles. For example:
- Security auditor flags "unsanitized user input" (exploitation angle)
- Data flow analyzer flags "missing input validation" (data correctness angle)
These are the SAME issue. Merge them:
- Use the most severe severity from any reporting agent
- Cross-reference which agents found it
- Preserve all perspectives (security + data flow insights)
- Do NOT lose any agent's unique insight
3. Conflict Resolution
If agents disagree:
- Agent A: "This is a bug" vs Agent B: "This is intentional"
- Flag as CONFLICTED
- Present both sides with evidence
- Let the devil's advocate (or human) resolve
4. Severity Normalization
Normalize all findings to the unified scale:
- CRITICAL: Will cause data loss, security breach, or system failure
- HIGH: Will cause significant user-facing errors or degradation
- MEDIUM: Will cause minor issues or maintenance burden
- LOW: Improvement opportunity, no immediate impact
- INFO: Observation, no action needed
5. Organization
Group findings by file, then by severity within each file. For each finding include:
- Description
- Severity (normalized)
- Affected files and lines
- Which specialist agent(s) found it
- Concrete fix suggestion
- Web verification status (VERIFIED/UNVERIFIED from agents)
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 · 157 lines · 107 tokens per session scan A 4456f593a870
synthesizer is an agent published in the GitHub repository bradwindy/ultimate-code-review (2 stars, last pushed 4mo ago), licensed MIT. It adds 107 tokens to every session and 1,115 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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