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 commands/abilityai/trinity/resumegit clone --depth 1 https://github.com/Abilityai/trinityWhat 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 | $0.00000 | $0.00381 |
| Opus 5 | $0.00000 | $0.00191 |
| Sonnet 5 | $0.00000 | $0.00076 |
| Haiku 4.5 | $0.00000 | $0.00038 |
Grade A, and why
resume 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST "http://backend:8000/api/ops/schedules/resume?agent_name={agent-name}" \ What it actually says
Resume Schedules
Resume previously paused schedules to restore automated executions.
Arguments
<agent-name>(optional) - Only resume schedules for this agentall- Resume all disabled schedules across all agents
Instructions
Resume All Schedules for an Agent
curl -X POST "http://backend:8000/api/ops/schedules/resume?agent_name={agent-name}" \
-H "Authorization: Bearer $TRINITY_MCP_API_KEY"
Resume All Schedules (Platform-wide)
curl -X POST "http://backend:8000/api/ops/schedules/resume" \
-H "Authorization: Bearer $TRINITY_MCP_API_KEY"
Response
The API returns:
{
"success": true,
"message": "Resumed X schedule(s)",
"resumed_count": X,
"agent_filter": "agent-name or null"
}
Report Format
## Schedules Resumed
Timestamp: {timestamp}
Action: Resumed {resumed_count} schedule(s)
Scope: {agent_name or "All agents"}
### What This Means
- Resumed schedules will execute according to their cron patterns
- Next execution times have been recalculated
- All automation restored to normal operation
### Verification
Use `/ops/schedules/list` to confirm schedules are enabled
Use Cases
- Post-Maintenance: Resume schedules after system updates complete
- Issue Resolved: Re-enable automation after debugging
- Selective Resume: Only resume specific agent's schedules
Notes
- Only resumes schedules that were previously enabled
- Does not affect schedules that were manually disabled by users
- Agent must be running for schedules to actually execute
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.
- 2d ago First seen · 67 lines · 0 tokens per session scan A 5936acbf5814
resume is a command published in the GitHub repository Abilityai/trinity (496 stars, last pushed 4d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 381 tokens. 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.