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 skills/synaptiai/agent-capability-standard/explainnpx skills add synaptiai/agent-capability-standard --skill explaingit clone --depth 1 https://github.com/synaptiai/agent-capability-standardWrote 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/synaptiai/agent-capability-standard/explain)<a href="https://agentmods.dev/skills/synaptiai/agent-capability-standard/explain"><img src="https://agentmods.dev/badge/skills/synaptiai/agent-capability-standard/explain.svg" alt="Measured on agentmods" 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 | $0.00032 | $0.02909 |
| Opus 5 | $0.00016 | $0.01455 |
| Sonnet 5 | $0.00006 | $0.00582 |
| Haiku 4.5 | $0.00003 | $0.00291 |
Grade A, and why
explain 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 — 335 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Intent
Generate a clear, structured explanation of a topic, decision, or concept tailored to the audience level. Include explicit assumptions, causal reasoning, and supporting evidence.
Success criteria:
- Explanation is clear and understandable by target audience
- Assumptions are explicitly stated
- Causal chain shows logical progression
- Evidence supports key claims
- No unnecessary jargon or fluff
Compatible schemas:
schemas/output_schema.yaml
Inputs
| Parameter | Required | Type | Description |
|---|---|---|---|
topic |
Yes | string or object | What to explain (concept, decision, code, etc.) |
audience_level |
No | string | beginner, intermediate, expert (default: intermediate) |
format |
No | string | prose, bullets, structured, diagram (default: structured) |
focus |
No | string | Specific aspect to emphasize |
max_length |
No | string | Length constraint (brief, standard, detailed) |
Procedure
-
Analyze the topic: Understand what needs explaining
- Identify the core concept or decision
- Note the complexity level
- Determine what background is needed
- Identify potential confusion points
-
Assess audience: Calibrate explanation depth
- Beginner: Define all terms, use analogies
- Intermediate: Assume basic knowledge, focus on key points
- Expert: Technical depth, skip fundamentals
-
Extract key concepts: Identify essential elements
- Core idea or decision
- Supporting concepts
- Technical terms that need definition
- Related concepts for context
-
Build causal chain: Show logical progression
- Starting conditions or premises
- Each step in reasoning
- How each step leads to the next
- Final conclusion
-
State assumptions: Make implicit knowledge explicit
- What must be true for explanation to hold
- Background knowledge assumed
- Simplifications made
- Edge cases not covered
-
Add analogies: Create relatable comparisons
- Match complexity to audience
- Use familiar domains
- Highlight key similarities
- Note where analogy breaks down
What ships with it
1 file 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.
- 4d ago First seen · 335 lines · 32 tokens per session scan A 6c9cbd2474a1
explain is a skill published in the GitHub repository synaptiai/agent-capability-standard (4 stars, last pushed 4d ago), licensed Apache-2.0. It adds 32 tokens to every session and 2,909 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 2026-08-31.
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