Agent Skill to Signal Write
Agent Skill to Signal Write is a verified SKILL blueprint on Promptally in Fullstack & Backend Engineering optimized for leading AI models. Emit structured agent signals — hands-up, blocked, done, checkpoint, partnership. Signals are written as JSON to .signals/ for dashboard consumption and noted in the journal for persistence. Available to explore, customize with pre-filled variables, and copy with zero authentication required.
Technical Specifications
| Specification | Value |
|---|---|
| Artifact type | SKILL (Fullstack & Backend Engineering) |
| Compatible engines | Universal / Model Agnostic |
| Input variables | None (pre-filled) |
| Approximate tokens | 1,326 |
| Source file | SKILL.md |
| Access tier | Free public (MIT) |
Pre-Filled Template
---
name: signal-write
description: 'Emit structured agent signals — hands-up, blocked, done, checkpoint, partnership. Signals are written as JSON to .signals/ for dashboard consumption and noted in the journal for persistence.'
---
# Agent Signals
Emit structured signals from a desk to the operator or other desks.
## When to use
- A desk needs operator attention (hands-up, blocked)
- Work is complete and ready for review (done)
- Significant progress worth noting (checkpoint)
- Two desks disagree and can't resolve it (hands-up)
- The TA is reporting coordination quality (partnership)
## Signal types
### `hands-up`
Two desks disagree and can't settle it against external facts.
This is the system working — the operator reads where desks
*disagree*, not where they perform confidence.
### `blocked`
A desk can't proceed without input — missing access, ambiguous
scope, need a decision only the operator can make.
### `done`
Work is complete and ready for review. Artifacts are on the bench.
### `checkpoint`
Significant progress worth the operator knowing about, but work
continues. Not blocked, not done — just a marker.
### `partnership`
Used by the TA (room coordinator) to report coordination quality.
Self-assessment scores reflect coordination, not code accuracy:
- **intent** — understood what the operator needed
- **confidence** — right work went to the right desks
- **accuracy** — dispatched work produced the right outcome
- **completeness** — nothing fell through the cracks
## How to emit
### 1. Write a JSON signal file to `.signals/`
This is the primary output — it's what the dashboard reads.
Create `desks/<desk-name>/.signals/<timestamp>.json` (for a desk in a
group folder, `<group>-desks/<desk-name>/.signals/<timestamp>.json`):
```json
{
"signal_type": "execution",
"subtype": "checkpoint",
"timestamp": "2026-07-19T21:30:00Z",
"run_id": "<optional; set to pair this with an outcome signal>",
"agent_name": "<desk-name>",
"self_assessment": {
"intent": 4,
"confidence": 5,
"accuracy": 4,
"completeness": 3
},
"patterns": {
"what_worked": "description of what went well",
"what_was_hard": "description of challenges",
"skill_gap": "areas for improvement"
},
"escalation": {
"reason": null,
"blocked_on": null,
"recommendation": null
}
}
```
### Signal type mapping
| Signal | `signal_type` | `subtype` |
|-----------|-----------------|----------------|
| hands-up | `"escalation"` | `"hands-up"` |
| blocked | `"escalation"` | `"blocked"` |
| done | `"execution"` | `"done"` |
| checkpoint| `"execution"` | `"checkpoint"` |
| partnership| `"partnership"` | `"partnership"`|
The `subtype` field preserves the specific signal state for
dashboard consumers. `signal_type` controls sort priority
(escalation → top).
> **Note:** The signals-dashboard canvas extension reads `subtype`
> when present and falls back to `signal_type` for display. If
> consuming signals in your own tooling, prefer `subtype` for the
> specific state.
> **Ordering:** include a `timestamp` (ISO 8601 UTC). The dashboard
> orders signals by it and falls back to file mtime only when it's
> absent — a git clone/checkout resets mtimes, so mtime alone is not a
> dependable clock.
### 2. Note the signal in the journal
Also append a short marker to the desk's journal for persistence:
```markdown
## <date> — [signal:<type>] <summary>
- <key details>
```
The journal note is the trail marker. The JSON file is the
machine-readable signal.
## Outcome signals (calibration)
The signals-dashboard can pair a desk's self-assessment with an
*outcome* — an independent rating of the realized result — and show
the **honesty gap** (how far the desk's confidence was from the
delivered quality). Outcome signals are optional and are usually
emitted by a reviewer/evaluator, not the desk itself.
Write them to the **same** `.signals/` directory:
```json
{
"signal_type": "outcome",
"run_id": "<same run_id as the signal it rates>",
"agent_name": "<reviewer name>",
"quality_rating": 4,
"effort_to_merge": "minimal",
"issues_found": ["optional short strings"],
"timestamp": "2026-07-19T22:00:00Z"
}
```
- **`run_id`** correlates an outcome with the execution/partnership
signal it rates — set the same `run_id` on both. If it's absent, the
dashboard falls back to the nearest outcome emitted shortly after the
latest signal.
- **`quality_rating`** (0–5) is the realized quality; the dashboard
compares it to the desk's self-assessed `confidence` to compute the
honesty gap.
- **`effort_to_merge`** — `"minimal"`, `"moderate"`, or `"significant"`.
- **`issues_found`** — optional array of short strings.
## Principles
- Signals are structured, not chatty. Short, factual, actionable.
- hands-up is not failure — it's the most valuable signal. It
means the system caught something one frame alone would have
missed.
- Don't signal for routine progress. Signals are for state
changes that affect the room, not status updates.
- blocked means truly blocked — not "I'd prefer input." If you
can proceed with a reasonable default, proceed and note it.
- Self-assessment scores should be honest, not optimistic. A 3/5
is fine. A 5/5 on everything is suspicious.
How to use this skill
- Review the pre-filled example and source files above.
- Copy the template or download
SKILL.md, then use it in your model, IDE, or workflow tool. - Compare your result with the sample output when one is provided.
Frequently Asked Questions
How do I use Agent Skill to Signal Write?
Open the skill on Promptally, review the pre-filled example, then copy the template or download SKILL.md and paste it into your model, IDE or workflow tool. Agent Skill to Signal Write is a static blueprint with no dynamic variables. Copy it and use it as-is.
Is Agent Skill to Signal Write free?
Yes. Agent Skill to Signal Write is free to view, copy and download on Promptally without creating an account. It is published under the MIT license.
What variables does Agent Skill to Signal Write need?
Agent Skill to Signal Write is a static blueprint with no dynamic variables. Copy it and use it as-is.