doc-diagrams-sequences

Mermaid sequence diagrams showing the order of calls between parts of up to three important processes. Mermaid is a text format that tools can turn into diagrams.

In plain words
What is it for?
Use it to document multi-step processes and the participants involved in each outbound call.
Why use it?
It makes the interaction between services or modules easier to follow than source code alone.

Agent for Claude Code

Install

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.

agentmods
npx agentmods add agents/theagenticguy/opencodehub/doc-diagrams-sequences
Clone the repo
git clone --depth 1 https://github.com/theagenticguy/opencodehub

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,437 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01437
Opus 5 $0.00000 $0.00718
Sonnet 5 $0.00000 $0.00287
Haiku 4.5 $0.00000 $0.00144

Measured 2d ago against content hash 965f2b1fb195, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

doc-diagrams-sequences 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 2d 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.

.claude/skills/codehub-document/templates/agents/doc-diagrams-sequences.md · 104 lines

How it starts

The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Packet · {{ repo }} · diagrams/behavioral/sequences.md

Conditional packet. The orchestrator only seeds this skeleton when {{ context_path }} § Top processes reports at least one process with ≥ 3 steps. If the condition is not met, the packet is skipped at seed time and no file is produced.

1. Objective

Produce {{ docs_root }}/diagrams/behavioral/sequences.md: up to three Mermaid sequenceDiagram blocks, one per top process, each showing the outbound call order across 4-8 participants.

2. Scope

  • Create: {{ docs_root }}/diagrams/behavioral/sequences.md
  • Do not touch: any other file under {{ docs_root }}/, any source file in the repo, .context.md, .prefetch.md, or any .packets/*.md other than this one.

3. Input specification

Source Read how Cache state
Shared context Read {{ context_path }} always first
Prefetch ledger Read {{ prefetch_path }} always first
Top processes (with step counts) {{ context_path }} § Top processes cached
Process step order mcp__codehub__context({symbol: <process-name>}) per top 3 processes mid-run
Participant labels mcp__codehub__query({text: <actor-name>}) when a step's symbol is ambiguous mid-run, on demand

4. Process

  1. Read {{ context_path }} and Read {{ prefetch_path }}. Confirm which processes in § Top processes have ≥ 3 steps — those are candidates.
  2. Pick the top 3 candidates by step count (ties broken by entry-point centrality from .context.md). If fewer than 3 qualify, emit only the qualifying count (1 or 2 diagrams).
  3. For each chosen process, call mcp__codehub__context({symbol: <process-name>}) and extract the outbound call sequence in dispatch order. Cache the digest in this packet's Work log.
  4. Derive 4-8 participant lifelines per process by grouping step targets into community / module bands. Lifelines are listed in dispatch order at the top of each sequenceDiagram.
  5. Draft each sequenceDiagram: solid arrows (->>) for synchronous calls, dashed (-->>) for returns. Short labels (≤ 15 chars on edges, ≤ 20 chars on participant names).
  6. If any single diagram exceeds 20 nodes (participants + step-labeled messages), keep the top-20 and move overflow into a ## Legend (overflow) table below that block.
  7. Write {{ docs_root }}/diagrams/behavioral/sequences.md with H1 = {{ repo }} · Sequences, one H2 per process, one fenced sequenceDiagram per H2.

Read the full file on GitHub · 104 lines

Changes

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.

  1. 2d ago First seen · 104 lines · 0 tokens per session scan A 965f2b1fb195

Subscribe to this mod's changes

doc-diagrams-sequences is an agent published in the GitHub repository theagenticguy/opencodehub (3 stars, last pushed 20d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,437 tokens. 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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