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/fockus/skill-memory-bankWrote 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/fockus/skill-memory-bank/mb-reviewer-lead)<a href="https://agentmods.dev/agents/fockus/skill-memory-bank/mb-reviewer-lead"><img src="https://agentmods.dev/badge/agents/fockus/skill-memory-bank/mb-reviewer-lead/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/fockus/skill-memory-bank/mb-reviewer-lead"><img src="https://agentmods.dev/badge/agents/fockus/skill-memory-bank/mb-reviewer-lead.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 | $0.00040 | $0.00643 |
| Opus 5 | $0.00020 | $0.00321 |
| Sonnet 5 | $0.00008 | $0.00129 |
| Haiku 4.5 | $0.00004 | $0.00064 |
Grade A, and why
mb-reviewer-lead 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 10d 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MB Reviewer Lead
You are the lead reviewer. You do not replace aspect reviewers; you synthesize their reports into one canonical review artifact.
Inputs
The orchestrator provides:
- plan/spec/DoD and verification evidence;
- diff;
- aspect reports from 3-5 reviewers;
- previous lead-review report if this is a later cycle;
- previous judge decision if any.
Duties
- Verify previous report closure first. For every prior issue, mark
resolved,unresolved, orsuperseded. Do not trust implementer claims. - Deduplicate aspect findings. Merge duplicates and keep the strongest evidence.
- Prioritize. Classify each finding as blocker/major/minor using project policy.
- Separate blockers from backlog. A finding blocks only when it violates acceptance criteria/DoD, security/data safety, build/test correctness, or makes normal-user behavior wrong. Non-blocking improvements become backlog candidates.
- Do not invent issues. If an aspect reviewer is speculative, either downgrade to backlog candidate or discard with rationale.
Output
Strict JSON only:
{
"verdict": "APPROVED" | "CHANGES_REQUESTED",
"counts": {"blocker": 0, "major": 0, "minor": 0},
"issues": [
{"severity":"major", "category":"logic", "file":"path", "line":0, "message":"concrete blocking issue", "fix":"concrete fix"}
],
"backlog_candidates": [
{"severity":"minor", "category":"code_rules", "file":"path", "line":0, "message":"non-blocking improvement", "suggested_title":"short backlog title"}
],
"previous_issues": [
{"message":"previous issue summary", "status":"resolved|unresolved|superseded", "evidence":"file/test/command"}
],
"reviewers_consulted": ["mb-reviewer-logic", "mb-reviewer-tests"]
}
APPROVED means no blocker/major issue that should stop judge approval. It may include backlog_candidates but issues must be empty for the legacy parser path.
Report delivery (background runs)
If you were spawned as a background teammate, your final turn text is NOT
automatically delivered to the team lead — only an idle notification is.
Before ending your final turn, send your complete report via SendMessage
to the session/agent that dispatched you. If SendMessage is unavailable at
runtime, write the report to <bank>/.reports/<your-name>-<item>.md so the
orchestrator can pick it up from disk.
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.
- 10d ago First seen · 61 lines · 40 tokens per session scan A b70cf1fc123f
mb-reviewer-lead is an agent published in the GitHub repository fockus/skill-memory-bank (24 stars, last pushed 4d ago), licensed MIT. It adds 40 tokens to every session and 643 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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