github-pr-stats

Data Community

Repo stars 0
Author repo skills-registry

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: Compute PR statistics (total, merged, closed, avg merge time, top contributor) from GitHub API data using Python or jq. Use when…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “Overview”, “Fetching PRs for a Date Range”, “Python: Compute Stats from JSON”, “Notes on State Values”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name github-pr-stats directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “Overview / Fetching PRs for a Date Range / Python: Compute Stats from JSON” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / write; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

GitHub PR Statistics

Overview

After fetching PR data from the GitHub API, use Python or jq to compute:

Total PR count
Merged vs closed counts
Average time-to-merge (days)
Top contributor by PR count

Fetching PRs for a Date Range

# Using gh search (handles pagination, date filtering)
gh pr list -R cli/cli \
  --search "created:2024-12-01..2024-12-31" \
  --state all \
  --limit 500 \
  --json number,author,createdAt,mergedAt,closedAt,state

Python: Compute Stats from JSON

import json
from datetime import datetime, timezone
from collections import Counter

# Load PR data (from gh pr list --json output)
with open('prs.json') as f:
    prs = json.load(f)

total = len(prs)

# Count merged vs closed-but-not-merged
merged = [pr for pr in prs if pr['mergedAt']]
closed = [pr for pr in prs if not pr['mergedAt'] and pr['state'] == 'CLOSED']

# Average time to merge (creation -> mergedAt), in days
def parse_dt(s):
    return datetime.fromisoformat(s.replace('Z', '+00:00'))

merge_days = []
for pr in merged:
    created = parse_dt(pr['createdAt'])
    merged_at = parse_dt(pr['mergedAt'])
    delta = (merged_at - created).total_seconds() / 86400
    merge_days.append(delta)

avg_merge_days = round(sum(merge_days) / len(merge_days), 1) if merge_days else 0.0

# Top contributor
authors = Counter(pr['author']['login'] for pr in prs)
top_contributor = authors.most_common(1)[0][0]

print(json.dumps({
    "total": total,
    "merged": len(merged),
    "closed": len(closed),
    "avg_merge_days": avg_merge_days,
    "top_contributor": top_contributor
}, indent=2))

Notes on State Values

gh pr list --json returns state as "OPEN", "CLOSED", or "MERGED"
mergedAt is non-null only for merged PRs
A PR with state == "CLOSED" and mergedAt == null is truly closed (not merged)

Notes on the Search API

created:2024-12-01..2024-12-31 is inclusive on both ends
Dec 31 means up to 2024-12-31T23:59:59Z
Use --limit 500 to avoid truncation for active repos

Source: cxcscmu/SkillLearnBench — distributed by TomeVault.

Fluxly profile Author and license come from source; runtime, permissions, and network are Fluxly detections or estimates

Fluxly category: Data
Author-declared agents: No explicit declaration found; this is not inferred or tested compatibility
Static check: 88 / 100 · heuristic scan, not runtime safety proof
Author / version / license: @tomevault-io · no license declared
Fluxly token estimate: Lean
Fluxly setup estimate: Plug-and-play
External API key: No requirement detected
Detected OS requirements: Unspecified
Runtime requirements: Python
Detected file/system behavior: Read-only
Write / modify
Detected network behavior: Local-only
Install commands: None (reference only)

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview github-pr-stats.preview

The current SKILL.md does not define a fixed output example.

SKILL.md SKILL.md

# GitHub PR Statistics

## Overview

After fetching PR data from the GitHub API, use Python or jq to compute:
- Total PR count
- Merged vs closed counts
- Average time-to-merge (days)
- Top contributor by PR count

## Fetching PRs for a Date Range

```bash
# Using gh search (handles pagination, date filtering)
gh pr list -R cli/cli \
  --search "created:2024-12-01..2024-12-31" \
  --state all \
  --limit 500 \
  --json number,author,createdAt,mergedAt,closedAt,state
```

## Python: Compute Stats from JSON

```python
import json
from datetime import datetime, timezone
from collections import Counter

# Load PR data (from gh pr list --json output)
with open('prs.json') as f:
    prs = json.load(f)

total = len(prs)

# Count merged vs closed-but-not-merged
merged = [pr for pr in prs if pr['mergedAt']]
closed = [pr for pr in prs if not pr['mergedAt'] and pr['state'] == 'CLOSED']

# Average time to merge (creation -> mergedAt), in days
def parse_dt(s):
    return datetime.fromisoformat(s.replace('Z', '+00:00'))

merge_days = []
for pr in merged:
    created = parse_dt(pr['createdAt'])
    merged_at = parse_dt(pr['mergedAt'])
    delta = (merged_at - created).total_seconds() / 86400
    merge_days.append(delta)

avg_merge_days = round(sum(merge_days) / len(merge_days), 1) if merge_days else 0.0

# Top contributor
authors = Counter(pr['author']['login'] for pr in prs)
top_contributor = authors.most_common(1)[0][0]

print(json.dumps({
    "total": total,
    "merged": len(merged),
    "closed": len(closed),
    "avg_merge_days": avg_merge_days,
    "top_contributor": top_contributor
}, indent=2))
```

## Notes on State Values

- `gh pr list --json` returns `state` as `"OPEN"`, `"CLOSED"`, or `"MERGED"`
- `mergedAt` is non-null only for merged PRs

…

Evidence boundary and execution chain

Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.

sections -> Overview → Fetching PRs for a Date Range → Python: Compute Stats from JSON → Notes on State Values → Notes on the Search API
terms    -> --- > Source: [cxcscmu/SkillLearnBench](https://github.com/cxcscmu/SkillLearnBench) — distributed by [TomeVault](https://tomevault.io).
files/cmd -> gh pr list --json · state · "OPEN" · "CLOSED" · "MERGED" · mergedAt · state == "CLOSED" · mergedAt == null
body sha256 -> 8ccfebd8b45d