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 skills add martineserios/thebrana --skill reviewgit clone --depth 1 https://github.com/martineserios/thebranaWrote 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/skills/martineserios/thebrana/review)<a href="https://agentmods.dev/skills/martineserios/thebrana/review"><img src="https://agentmods.dev/badge/skills/martineserios/thebrana/review/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/skills/martineserios/thebrana/review"><img src="https://agentmods.dev/badge/skills/martineserios/thebrana/review.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 | $0.00035 | $0.04566 |
| Opus 5.5 | $0.00014 | $0.01826 |
| Sonnet 5.5 | $0.00007 | $0.00913 |
| Haiku 4.5 | $0.00003 | $0.00457 |
Grade A, and why
review 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 1mo 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 — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review — Business Health
Unified business review skill. Replaces /weekly-review, /monthly-close, /monthly-plan, and /growth-check.
On entry, create a CC Task step registry. Follow the guided-execution protocol.
Register these steps: LOAD, REVIEW (subcommand-specific), EXTRACT, EVALUATE, PERSIST.
ToolSearch("select:mcp__ruflo__memory_search,mcp__ruflo__memory_store")
Step 0 — LOAD
Pull relevant business context into memory before the review. Budget: 30K tokens max.
- Build query from available context:
"{project} {task.subject} {task.tags joined} {user_input}" - Primary — ruflo MCP (run all in parallel —
namespace: "all"only returns session records):
Merge results, rank by similarity. Focus on: prior review snapshots (namespace: business), pipeline state, event log entries, and health metrics. 2b. Graph edge traversal — seemcp__ruflo__memory_search(query: "{query} metrics revenue health pipeline", namespace: "knowledge", limit: 2, threshold: 0.4) mcp__ruflo__memory_search(query: "{query} metrics revenue health pipeline", namespace: "pattern", limit: 2, threshold: 0.4) mcp__ruflo__memory_search(query: "{query} metrics revenue health pipeline", namespace: "business", limit: 3, threshold: 0.4)build.mdLOAD step 2b. Followdepends_on/informsedges from knowledge results. Max 3 graph-derived docs. Best-effort, never blocks. - Fallback — tag-based grep (if MCP unavailable):
Read the most recent review file and top 2 matching dimension files (first 80 lines each).grep -rl "{keywords}" docs/reviews/ --include="*.md" | head -5 grep -rl "{keywords}" ~/enter_thebrana/brana-knowledge/dimensions/ --include="*.md" | head -3 - Skill match handling — if any result has
namespace: "skills"and score >= 0.5, mention inline: "Matching skill: /brana:{name} ({score})." Informational only — don't auto-invoke or block. 4a. JIT skill acquisition — if no skills match and topic involves a specific technology, offer marketplace search viaSkill(skill="brana:acquire-skills", args="{tech}"). Read installed procedure into context immediately. Seebuild.mdLOAD step 4a for full logic and guard rails. - Summarize loaded knowledge as a brief context preamble (2-5 bullets). Surface prior trends, last review's bottleneck, and pipeline status so the review builds on history.
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.
- 1mo ago First seen · 400 lines · 35 tokens per session scan A ac2212475d96
review is a skill published in the GitHub repository martineserios/thebrana (3 stars, last pushed yesterday), licensed MIT. It adds 35 tokens to every session and 4,566 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
Other skills, from other repositories
github-issue-triage
A GitHub issue organiser for open problems and requests in a software project. GitHub is a service where teams store code and track issues.
Customer Success Manager
Manage customer relationships, track health scores, prevent churn, and drive expansion.
Advisory Board Builder
Recruit, structure, and manage advisory boards for strategic guidance.
Affiliate Marketing Manager
Set up and manage affiliate marketing programs for growth and revenue.
Board Meeting Prep
Prepare board meeting decks, updates, and materials for effective governance.
Client Onboarding Designer
Design smooth client onboarding experiences that ensure success and retention.