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 skills/implicit-labs/autosymph/verify-finalizenpx skills add implicit-labs/autosymph --skill verify-finalizegit clone --depth 1 https://github.com/implicit-labs/autosymphWhat 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 | $0.00069 | $0.01371 |
| Opus 5 | $0.00034 | $0.00685 |
| Sonnet 5 | $0.00014 | $0.00274 |
| Haiku 4.5 | $0.00007 | $0.00137 |
Grade A, and why
verify-finalize 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.
parsing + table-building without hitting real Linear (curl is PATH-stubbed How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
verify-finalize
The verify agent's ONLY end-action. Build a manifest, call this script. Done.
Why this skill exists
verify-completion-audit gives deterministic detection of "the agent took
screenshots and uploaded none." Detection alone is not enough: prompt-only
enforcement can still be skipped during a long verify run.
This skill replaces the discipline rule with a mechanical can't-skip-it:
the agent's only end-action is calling verify-finalize.sh. The script
handles upload + post atomically. The agent CAN'T forget — there's no
separate sub-step to forget.
When to use
Always, as the LAST tool call of every verify run. Replaces:
- All direct
mcp__linear__create_attachmentcalls - The single
mcp__linear__save_commentcall with the summary table
If preflight (Phase 0) blocked verify before iOS work, you still call verify-finalize with the BLOCKED-marked items. There's never a verify run that should NOT end with verify-finalize.
Manifest schema
JSON file. Required fields: issue_id, session_name, result, items.
Optional: minor_fixes_applied.
{
"issue_id": "ISSUE-123",
"session_name": "ISSUE-123-verify-run14",
"result": "complete",
"minor_fixes_applied": "none",
"items": [
{
"n": 1,
"item": "swift build passes",
"method": "cli",
"status": "PASS",
"evidence": "exit code 0"
},
{
"n": 6,
"item": "Header in Text mode",
"method": "ios-simulator + video",
"status": "PASS",
"evidence_path": "<workspace>/verify-1.mp4",
"evidence_kind": "video"
},
{
"n": 12,
"item": "Dynamic Type largest size",
"method": "screenshot",
"status": "PASS",
"evidence_path": "<workspace>/verify-2.png",
"evidence_kind": "image"
},
{
"n": 8,
"item": "iOS chrome",
"method": "ios-simulator + video",
"status": "BLOCKED",
"evidence": "preflight: idb broken (pyexpat ImportError)"
},
{
"n": 16,
"item": "Aesthetic match vs design ref",
"method": "human",
"status": "SKIPPED: human-only"
}
]
}
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 150 lines · 69 tokens per session scan A c963b882e53d
verify-finalize is a skill published in the GitHub repository implicit-labs/autosymph (5 stars, last pushed 8d ago), licensed MIT. It adds 69 tokens to every session and 1,371 once invoked, about $0.0003 per session on Opus 5. 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 2026-08-31.
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