findings-to-github-issues

Original：🇺🇸 English

Translated

End-to-end orchestrator that turns findings from ANY input (audit spreadsheet, code/security review, QA report, meeting notes, a pasted list of issues) into a GitHub Issues backlog with a milestone, labels, and a tracking issue. Drives the sibling github-backlog skills in order with safety gates. Trigger whenever the user says "turn this audit/spreadsheet/review/list of issues into GitHub issues", "create a backlog from these findings", "file these as GitHub issues", "import this xlsx/csv into GitHub", "make issues from this report", or hands you a source document and asks for it to land in GitHub. This is the headline, one-shot entry point (/github-backlog:run wraps it). Not for editing existing issues individually.

4installs

Sourcethodsaphonsonthiphin/workflow-daily-work

Added on2026-08-29

NPX Install

npx skill4agent add thodsaphonsonthiphin/workflow-daily-work findings-to-github-issues

SKILL.md Content

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findings-to-github-issues (orchestrator)

Run the full pipeline: a source document in, a GitHub Issues backlog out. You coordinate six sibling skills; each owns its step and its data contract. Your job is to sequence them, keep the working files together, and enforce the safety gates so nothing irreversible happens without the user seeing it first.

Why an orchestrator: the value is in the gates. Creating issues is a write the user cannot easily undo (close is manual; notifications already fired), so the pipeline is deliberately staged: read-only extraction and classification first, a visual dry-run that creates nothing, an explicit human approval, then the real write.

Data flow

extract-findings         -> findings.json
classify-github-issues   -> github_backlog_input.json  (consumed by create_github_issues.py)
github-create-issues     -> github_backlog_result.json (consumed by github_tracking.py)

Working directory: create one beside the source and keep all JSON files there.

Process

0. Prereqs + auth (recommended on first run)

powershell

powershell -ExecutionPolicy Bypass -File "${CLAUDE_PLUGIN_ROOT}/scripts/setup_check_github.ps1"

Checks gh CLI, Python + requests + openpyxl,

GH_OWNER

/

GH_REPO

, and repo reachability. For auth specifics, delegate to github-auth.

1. Extract →

findings.json

(delegate to extract-findings)

Have extract-findings read the source and normalize it to

findings.json

. Confirm the column mapping with the user before moving on — which column is the

key

, which are

current

/

expected

, where

severity

and

status

come from.

2. Triage → scoped subset (delegate to triage-findings)

Have triage-findings filter

findings.json

to the wave worth creating now. Recommend Critical + confirmed first. Hold

needs-review

for a later wave.

3. Classify →

github_backlog_input.json

(delegate to classify-github-issues)

Have classify-github-issues map the scoped findings to GitHub Issues with labels, milestone, body, and size estimate. It will show an estimates table.

GATE — estimates. Show the table and get the user's OK / adjustments before the visual dry-run.

4. VISUAL DRY-RUN → validate, create nothing (delegate to github-create-issues)

Have github-create-issues render

github_backlog_input.json

as a formatted table — title, labels, milestone, assignee per item. Nothing is created.

GATE — stop here. Do not proceed until the user has explicitly approved the list. Present the count, the milestone, and the labels, and wait for a clear yes.

5. REAL RUN →

github_backlog_result.json

(delegate to github-create-issues)

Only after approval. The script creates labels, the milestone, each issue, then the tracking issue:

powershell

$env:GH_OWNER = "Cartagena365"
$env:GH_REPO  = "GlassHull"
python "${CLAUDE_PLUGIN_ROOT}/scripts/create_github_issues.py" `
  --input  "<workdir>/github_backlog_input.json" `
  --output "<workdir>/github_backlog_result.json"

Then verify the created items — confirm each

key

got a

number

and

url

in

github_backlog_result.json

, and surface any that failed.

6. Write-back tracking — spreadsheets only (delegate to github-writeback-tracking)

Only if the source is a spreadsheet.

GATE — back up the source first.

Have github-writeback-tracking drive

github_tracking.py

: first

add-columns

, then

writeback

. Both subcommands are idempotent.

7. Report back

Summarize the run:

Created: count + clickable links + tracking issue link.
Held / skipped: the triage wave deferred, plus any real-run errors.
Follow-ups: the obvious next wave.

Safety gates (non-negotiable)

Visual dry-run before real run — step 4 always precedes step 5.
Explicit approval before any write — never jump from classification to creation.
Back up the source before write-back — step 6 edits the file in place.

findings-to-github-issues

NPX Install

Tags

SKILL.md Content

findings-to-github-issues (orchestrator)

Data flow

Process

0. Prereqs + auth (recommended on first run)

1. Extract →
`findings.json`
(delegate to extract-findings)

2. Triage → scoped subset (delegate to triage-findings)

3. Classify →
`github_backlog_input.json`
(delegate to classify-github-issues)

4. VISUAL DRY-RUN → validate, create nothing (delegate to github-create-issues)

5. REAL RUN →
`github_backlog_result.json`
(delegate to github-create-issues)

6. Write-back tracking — spreadsheets only (delegate to github-writeback-tracking)

7. Report back

Safety gates (non-negotiable)

findings-to-github-issues

NPX Install

Tags

SKILL.md Content

findings-to-github-issues (orchestrator)

Data flow

Process

0. Prereqs + auth (recommended on first run)

1. Extract → findings.json (delegate to extract-findings)

2. Triage → scoped subset (delegate to triage-findings)

3. Classify → github_backlog_input.json (delegate to classify-github-issues)

4. VISUAL DRY-RUN → validate, create nothing (delegate to github-create-issues)

5. REAL RUN → github_backlog_result.json (delegate to github-create-issues)

6. Write-back tracking — spreadsheets only (delegate to github-writeback-tracking)

7. Report back

Safety gates (non-negotiable)

1. Extract →
`findings.json`
(delegate to extract-findings)

3. Classify →
`github_backlog_input.json`
(delegate to classify-github-issues)

5. REAL RUN →
`github_backlog_result.json`
(delegate to github-create-issues)