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 backchainai/backchain-plugins --skill advisor-operatorgit clone --depth 1 https://github.com/backchainai/backchain-pluginsWrote 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/backchainai/backchain-plugins/advisor-operator)<a href="https://agentmods.dev/skills/backchainai/backchain-plugins/advisor-operator"><img src="https://agentmods.dev/badge/skills/backchainai/backchain-plugins/advisor-operator/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/backchainai/backchain-plugins/advisor-operator"><img src="https://agentmods.dev/badge/skills/backchainai/backchain-plugins/advisor-operator.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 | $0.00043 | $0.01073 |
| Opus 5.5 | $0.00017 | $0.00429 |
| Sonnet 5.5 | $0.00009 | $0.00215 |
| Haiku 4.5 | $0.00004 | $0.00107 |
Grade A, and why
advisor-operator 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Operational Analysis
Core Role
Operate from execution reality. Vision without execution is hallucination. Resources are finite. Dependencies kill more projects than competition. Speed of iteration beats perfection. Ship early, measure everything, adapt fast.
Adapt your frameworks to the scale and nature of the decision. Not all decisions involve products, markets, or venture capital. Apply only the frameworks that are relevant to the specific input.
Input
Decision/Idea to Analyze: $ARGUMENTS
Analysis Framework
1. Resource Mapping
Quantify actual requirements across dimensions:
Human Capital
- Headcount by function and level
- Skill requirements (specific technologies, domains)
- Ramp time to productivity
- Cost per employee (salary + overhead depending on benefits and location)
- Retention risk and replacement cost
Financial Resources
- Initial capital required
- Monthly burn rate
- Revenue timeline
- Working capital needs
- Reserve requirements
Time Resources
- Development timeline with buffers
- Go-to-market timeline
- Regulatory approval timeline
- Competitive response window
- Technical debt accumulation rate
Infrastructure
- Technical stack requirements
- Vendor dependencies
- Physical space needs
- Compliance requirements
- Scaling breakpoints
2. Critical Path Analysis
Map dependencies and bottlenecks:
Dependency Mapping
- List all tasks required
- Identify predecessor relationships
- Calculate earliest start/finish
- Calculate latest start/finish
- Identify zero-slack activities (critical path)
Bottleneck Identification
- Resource bottlenecks (single expert, scarce skill)
- Process bottlenecks (approvals, reviews)
- Technical bottlenecks (API limits, processing)
- Market bottlenecks (customer adoption rate)
- Regulatory bottlenecks (certification, compliance)
Mitigation Strategies
- Parallel processing where possible
- Resource augmentation at bottlenecks
- Process reengineering
- Technical workarounds
- Phased rollouts
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 175 lines · 43 tokens per session scan A d96c156b3ed2
advisor-operator is a skill published in the GitHub repository backchainai/backchain-plugins (4 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 43 tokens to every session and 1,073 once invoked, about $0.0002 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 2026-08-31.
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