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/ashkaan/contextium/explainnpx skills add Ashkaan/contextium --skill explaingit clone --depth 1 https://github.com/Ashkaan/contextiumWhat 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 | $0.02805 |
| Opus 5 | $0.00016 | $0.01403 |
| Sonnet 5 | $0.00006 | $0.00561 |
| Haiku 4.5 | $0.00003 | $0.00281 |
Grade A, and why
explain scanned grade A with 1 finding 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 yesterday.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **External concepts**: use WebSearch/WebFetch. These are out of the `research-agent`'s scope — it reads this repo, not the internet. When you already know the URL, fetch it with `curl` and read the page yourself: WebFe How it starts
The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explain — Deep Research & Root Cause Analysis
Investigate a topic until confident in root cause or core understanding. Produce an actionable executive summary plus deeper analysis.
Step graph (mirrors frontmatter steps:): step-0-validate-input → step-1-classify-complexity → step-2-frame → step-3-research → step-4-synthesize → step-5-next-action-gate
Critical
- Validate input first. If
$ARGUMENTSis empty or too vague, ask ONE clarifying question before launching research. Vague input wastes parallel-agent budget on the wrong target. - A class-level flaw becomes work, by default. If the explanation identifies a flaw in a shared mechanism (one affecting several files), the Step 5
AskUserQuestiondefault option is "Ship class fix now" per@rule:class-fix-is-atomic. Do NOT silently end at explanation — surface the chain.
step-0-validate-input
If $ARGUMENTS is empty or too vague, ask ONE clarifying question first. Do not
launch research on an ambiguous target.
step-1-classify-complexity
- Quick — well-scoped factual, single concept. Skip to Step 4 using own knowledge + one targeted lookup if needed.
- Standard — requires tracing code/docs/external sources; single likely answer. Steps 2-4 sequentially.
- Deep — cross-cutting, multiple possible causes, systems-level "why". Steps 2-4 with parallel research agents.
State the classification and a one-sentence restatement before proceeding.
step-2-frame
INVESTIGATION FRAME:
- Question: [precise restatement]
- Type: [concept | root-cause | failure-mode | design-rationale | comparison]
- Scope: [in scope vs out of scope]
- Hypotheses: [1-3 ranked by likelihood]
- Key unknowns: [what confirms/rejects each]
If the question references files, a project, or recent work, pull context (read files, git log). If it references a production incident, gather the same context you would to explain it — logs, the recent diff, the alert itself — but do not start fixing: this skill's job is to say WHY, and the fix is a separate decision someone should make with the explanation in hand.
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.
- yesterday First seen · 205 lines · 32 tokens per session scan A 06c8fb8d1985
explain is a skill published in the GitHub repository Ashkaan/contextium (32 stars, last pushed 4d ago), licensed MIT. It adds 32 tokens to every session and 2,805 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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