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/dr-code/tessera/dispatching-parallel-agentsnpx skills add dr-code/tessera --skill dispatching-parallel-agentsgit clone --depth 1 https://github.com/dr-code/tesseraWhat 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 | $0.00026 | $0.00673 |
| Opus 5 | $0.00013 | $0.00336 |
| Sonnet 5 | $0.00005 | $0.00135 |
| Haiku 4.5 | $0.00003 | $0.00067 |
Grade A, and why
dispatching-parallel-agents 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 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.
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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dispatching Parallel Agents
Overview
When you have multiple unrelated failures (different test files, different subsystems, different bugs), investigate them concurrently.
Core principle: Dispatch one agent per independent problem domain. Let them work concurrently.
When to Use
- 3+ test files failing with different root causes
- Multiple subsystems broken independently
- Each problem can be understood without context from others
- No shared state between investigations
Don't use when:
- Failures are related (fix one might fix others)
- Agents would interfere with each other (same files, same resources)
Tessera Context Load
Before dispatching any agents — if tessera MCP is configured:
1. graph_continue (mandatory first call for the coordinator)
2. graph_retrieve with the failing component names as query
This routes the coordinator to the most relevant files for understanding the problem space before splitting work into agents.
The Pattern
1. Identify Independent Domains
Group failures by what's broken:
- File A tests: one component
- File B tests: different component
- File C tests: yet another component
Each domain is independent.
2. Create Focused Agent Tasks
Each agent gets:
- Specific scope: One test file or subsystem
- Clear goal: Make these tests pass
- Constraints: Don't change other code
- Expected output: Summary of what you found and fixed
Include the Tessera graph discipline in each agent prompt (if tessera MCP is configured):
- Call graph_continue as your FIRST tool call
- Call graph_retrieve with this task's key terms
- Read recommended_files via graph_read before exploring
- After each file edit: graph_register_edit(files=["file::symbol"], summary="...")
- Lock architectural choices: graph_lock_decision(summary, scope, files)
3. Dispatch in Parallel
Use Task tool — all dispatches in a single message so they run concurrently.
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 · 105 lines · 26 tokens per session scan A fcee0f679d3f
dispatching-parallel-agents is a skill published in the GitHub repository dr-code/tessera (1 stars, last pushed 21d ago), licensed MIT. It adds 26 tokens to every session and 673 once invoked, about $0.0001 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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