Target Workflow
Daily AI Poem — selected as the highest-AIC workflow not optimized in the last 14 days (last optimization: 2026-07-17). All higher-AIC workflows were optimized more recently.
Analysis Period
2026-07-25 → 2026-07-31 · 6 runs audited
Spend Profile
| Metric |
Value |
| Runs analyzed |
6 (5 success, 1 failure) |
| Total AIC |
79.60 |
| Avg AIC / run (successful) |
~15.92 |
| Total action minutes |
32 min (avg ~5.3 min/run) |
| Total tokens |
not tracked (null across all runs) |
| Avg turns / run |
not tracked |
| Cache efficiency |
indeterminate (no token breakdown) |
| Failure rate |
16.7% (1/6 runs) |
Ranked Recommendations
1. Investigate and handle token-guardrail failures (Reliability)
Estimated AIC savings: ~0 AIC/run in AI credits; saves ~2 CI-minutes per failed run
Run §30151984839 was cancelled on 2026-07-25 because the "Check daily workflow token guardrail" step failed. The job was marked cancelled before any AI invocation occurred, so no AI credits were consumed — but 2 action-minutes were wasted and the daily poem was not published.
Action: Audit the token-guardrail configuration (daily quota thresholds) to ensure it accounts for the expected per-run AIC of ~16 credits. If the guardrail is intentionally restrictive, add a workflow_dispatch fallback or a retry step so a transient quota spike doesn't silently skip the day's poem.
Evidence: Job conclusion cancelled, step Check daily workflow token guardrail → failure, run duration 1 min (vs. avg 4.7 min for successful runs), AIC = null (no AI call made).
2. Consolidate the Instructions section (Prompt efficiency)
Estimated AIC savings: ~1–1.5 AIC/run (~6–9%)
The current ## Instructions section contains three levels of nesting: a numbered list (3 steps), a sub-bullet list (4 qualities inside step 2), and a separate formatting constraint. Much of this is stylistic guidance that repeats intent already stated in the workflow description ("witty poet and technologist") and the theme list.
Concrete action: Merge the qualities bullet list into a single imperative sentence and collapse steps 1–3 into a tighter paragraph. Example condensed version:
## Instructions
Use today's date (day-of-month mod 7) to select a theme from the list above.
Write 3–4 stanzas (4 lines each) with a clear, playful voice — concrete details, authentic developer humour, rhythm over forced rhyme.
Give the poem a punchy title (3–8 words) and add a one-sentence Inspiration Note explaining the theme choice.
This removes ~120–150 tokens of instruction overhead per run while preserving all behavioural constraints.
Evidence: Successful runs produce correctly-structured poems without variation, indicating the detailed sub-bullets are not driving differentiation — the model follows the high-level intent regardless.
3. Simplify theme-rotation computation (Prompt efficiency)
Estimated AIC savings: ~0.5 AIC/run (~3%)
The prompt instructs the agent to compute day_of_month mod 7 to select a theme. This is a small but unnecessary arithmetic step that consumes reasoning tokens. Since the agent always has access to today's date via the environment context, the formula can be pre-resolved.
Concrete action: Replace the formula instruction with a direct lookup table comment, or simply remove the formula and instruct the agent to rotate freely while maintaining variety. If strict rotation is required, consider injecting the pre-computed theme index via the workflow's environment step before the agent runs.
Evidence: The mod-7 instruction adds a computational prefix to every generation turn with no observable quality benefit — all 5 successful runs produced varied poems regardless of strict formula adherence.
Caveats
- Token counts are
null for all runs, so cache efficiency and per-turn token spend cannot be measured directly. Savings estimates are derived from prompt character counts and typical model pricing ratios.
- Only 6 runs were available (7-day window). The single failure was pre-AI (guardrail), so it does not indicate model-level instability.
- This is a low-AIC workflow (~15.92/run); absolute savings are modest (~2 AIC/run if all recommendations implemented). The primary value is reliability (ensuring the poem publishes every day).
Run evidence table
Generated by Agentic Workflow AIC Usage Optimizer · 194.6 AIC · ⊞ 21.6K · ◷
Target Workflow
Daily AI Poem — selected as the highest-AIC workflow not optimized in the last 14 days (last optimization: 2026-07-17). All higher-AIC workflows were optimized more recently.
Analysis Period
2026-07-25 → 2026-07-31 · 6 runs audited
Spend Profile
Ranked Recommendations
1. Investigate and handle token-guardrail failures (Reliability)
Estimated AIC savings: ~0 AIC/run in AI credits; saves ~2 CI-minutes per failed run
Run §30151984839 was cancelled on
2026-07-25because the "Check daily workflow token guardrail" step failed. The job was markedcancelledbefore any AI invocation occurred, so no AI credits were consumed — but 2 action-minutes were wasted and the daily poem was not published.Action: Audit the token-guardrail configuration (daily quota thresholds) to ensure it accounts for the expected per-run AIC of ~16 credits. If the guardrail is intentionally restrictive, add a
workflow_dispatchfallback or a retry step so a transient quota spike doesn't silently skip the day's poem.Evidence: Job conclusion
cancelled, stepCheck daily workflow token guardrail→failure, run duration 1 min (vs. avg 4.7 min for successful runs), AIC = null (no AI call made).2. Consolidate the Instructions section (Prompt efficiency)
Estimated AIC savings: ~1–1.5 AIC/run (~6–9%)
The current
## Instructionssection contains three levels of nesting: a numbered list (3 steps), a sub-bullet list (4 qualities inside step 2), and a separate formatting constraint. Much of this is stylistic guidance that repeats intent already stated in the workflow description ("witty poet and technologist") and the theme list.Concrete action: Merge the qualities bullet list into a single imperative sentence and collapse steps 1–3 into a tighter paragraph. Example condensed version:
This removes ~120–150 tokens of instruction overhead per run while preserving all behavioural constraints.
Evidence: Successful runs produce correctly-structured poems without variation, indicating the detailed sub-bullets are not driving differentiation — the model follows the high-level intent regardless.
3. Simplify theme-rotation computation (Prompt efficiency)
Estimated AIC savings: ~0.5 AIC/run (~3%)
The prompt instructs the agent to compute
day_of_month mod 7to select a theme. This is a small but unnecessary arithmetic step that consumes reasoning tokens. Since the agent always has access totoday's datevia the environment context, the formula can be pre-resolved.Concrete action: Replace the formula instruction with a direct lookup table comment, or simply remove the formula and instruct the agent to rotate freely while maintaining variety. If strict rotation is required, consider injecting the pre-computed theme index via the workflow's environment step before the agent runs.
Evidence: The mod-7 instruction adds a computational prefix to every generation turn with no observable quality benefit — all 5 successful runs produced varied poems regardless of strict formula adherence.
Caveats
nullfor all runs, so cache efficiency and per-turn token spend cannot be measured directly. Savings estimates are derived from prompt character counts and typical model pricing ratios.Run evidence table