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 skills add pilotspace/pilot-space --skill generate-digestgit clone --depth 1 https://github.com/pilotspace/pilot-spaceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/pilotspace/pilot-space/generate-digest)<a href="https://agentmods.dev/skills/pilotspace/pilot-space/generate-digest"><img src="https://agentmods.dev/badge/skills/pilotspace/pilot-space/generate-digest/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pilotspace/pilot-space/generate-digest"><img src="https://agentmods.dev/badge/skills/pilotspace/pilot-space/generate-digest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00012 | $0.00766 |
| Opus 5.5 | $0.00005 | $0.00306 |
| Sonnet 5.5 | $0.00002 | $0.00153 |
| Haiku 4.5 | $0.00001 | $0.00077 |
Grade A, and why
generate-digest 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Digest Skill
Analyze workspace activity and generate categorized, actionable suggestions for the AI Digest panel.
Quick Start
Use this skill when:
- Hourly background job triggers digest generation
- User manually refreshes the digest panel
- System detects significant workspace state changes
Workflow
-
Receive Workspace Context
- Recent issues (last 7 days): state, assignee, priority, activity
- Recent notes (last 7 days): annotations, extraction status
- Active cycles: progress metrics, burndown
- Issue links and dependencies
-
Analyze for Actionable Insights Categories to check:
stale_issues: Issues not updated in 3+ days while in active stateunlinked_notes: Notes with no linked issues (potential extraction candidates)review_needed: Issues in review state for 2+ daysblocked_dependencies: Issues blocked by unresolved dependenciescycle_risk: Cycles at risk of missing targets (>70% time, <50% done)overdue_items: Issues past target dateunassigned_priority: High/urgent priority issues with no assigneeduplicate_candidates: Issues with high semantic similaritystale_prs: PRs open for 3+ days without reviewannotation_pending: Notes with unaddressed AI annotationsinactive_members: Team members with no activity in 5+ daysdocumentation_gaps: Features without linked documentation notes
-
Score Relevance For each suggestion, score 0.0-1.0 based on:
- Ownership: Is the user the owner/assignee? (+0.3)
- Recency: How recently did the user interact with related items? (+0.2)
- Priority: Is the related item high/urgent priority? (+0.2)
- Impact: Does this affect active cycles or deadlines? (+0.3)
-
Return Structured Output
Output Format
{
"suggestions": [
{
"id": "uuid",
"category": "stale_issues",
"title": "3 issues haven't been updated this week",
"description": "PS-42, PS-55, PS-61 are in progress but have no activity since Monday",
"entity_id": "uuid",
"entity_type": "issue",
"action_url": "/workspace/issues?filter=stale",
"relevance_score": 0.85
}
],
"summary": "Generated 8 suggestions across 5 categories",
"tokens_used": {
"input": 950,
"output": 420
}
}
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.
- 2mo ago First seen · 93 lines · 12 tokens per session scan A 2d7d258ba096
generate-digest is a skill published in the GitHub repository pilotspace/pilot-space (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 12 tokens to every session and 766 once invoked, about $0.0000 per session on Opus 5.5. 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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